{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NOTEBOOK_HEADER-->\n",
    "*This notebook contains course material from [CBE40455](https://jckantor.github.io/CBE40455) by\n",
    "Jeffrey Kantor (jeff at nd.edu); the content is available [on Github](https://github.com/jckantor/CBE40455.git).\n",
    "The text is released under the [CC-BY-NC-ND-4.0 license](https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode),\n",
    "and code is released under the [MIT license](https://opensource.org/licenses/MIT).*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Machine Bottleneck](http://nbviewer.jupyter.org/github/jckantor/CBE40455/blob/master/notebooks/04.02-Machine-Bottleneck.ipynb) | [Contents](toc.ipynb) | [Jesuit Volunteer Corps](http://nbviewer.jupyter.org/github/jckantor/CBE40455/blob/master/notebooks/04.04-Jesuit-Volunteer-Corps.ipynb) ><p><a href=\"https://colab.research.google.com/github/jckantor/CBE40455/blob/master/notebooks/04.03-Job-Shop-Scheduling.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a><p><a href=\"https://raw.githubusercontent.com/jckantor/CBE40455/master/notebooks/04.03-Job-Shop-Scheduling.ipynb\"><img align=\"left\" src=\"https://img.shields.io/badge/Github-Download-blue.svg\" alt=\"Download\" title=\"Download Notebook\"></a>"
   ]
  },
  {
   "attachments": {
    "jobshopdiagram.jpg": {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Job Shop Scheduling"
   ]
  },
  {
   "attachments": {
    "jobshopdiagram.jpg": {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background\n",
    "\n",
    "A job shop consists of a set of distinct machines that process jobs. Each job is a series of tasks that require use of particular machines for known durations, and which must be completed in specified order. The job shop scheduling problem is to schedule the jobs on the machines to minimize the time necessary to process all jobs (i.e, the makespan) or some other metric of productivity. Job shop scheduling is one of the classic problems in Operations Research. \n",
    "\n",
    "Data consists of two tables. The first table is decomposition of the jobs into a series of tasks. Each task lists a job name, name of the required machine, and task duration. The second table list task pairs where the first task must be completed before the second task can be started. This formulation is quite general, but can also specify situations with no feasible solutions.  "
   ]
  },
  {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Job Shop Example\n",
    "\n",
    "The following example of a job shop is from from Christelle Gueret, Christian Prins, Marc Sevaux, \"Applications of Optimization with Xpress-MP,\" Dash Optimization, 2000.\n",
    "\n",
    "In this example, there are three printed paper products that must pass through color printing presses in a particular order. The given data consists of a flowsheet showing the order in which each job passes through the color presses\n",
    "\n",
    "![jobshopdiagram.jpg](attachment:jobshopdiagram.jpg)\n",
    "\n",
    "and a table of data showing, in minutes, the amount of time each job requires on each machine.\n",
    "\n",
    "| Machine | Color | Paper 1 | Paper 2 | Paper 3 |\n",
    "| :-----: | :---: | :-----: | :-----: | :-----: |\n",
    "| 1       | Blue  | 45      | 20      | 12      |\n",
    "| 2       | Green | -       | 10      | 17      |\n",
    "| 3       | Yellow| 10      | 34      | 28      |\n",
    "\n",
    "What is the minimum amount of time (i.e, what is the makespan) for this set of jobs?"
   ]
  },
  {
   "attachments": {
    "jobshopdiagram.jpg": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Task Decomposition\n",
    "\n",
    "The first step in the analysis is to decompose the process into a series of tasks. Each task is a (job,machine) pair. Some tasks cannot start until a prerequisite task is completed.\n",
    "\n",
    "| Task (Job,Machine) | Duration | Prerequisite Task |\n",
    "| :----------------: | :------: | :---------------: |\n",
    "| (Paper 1, Blue)    | 45       | -                 |\n",
    "| (Paper 1, Yellow)  | 10       | (Paper 1,Blue)    |\n",
    "| (Paper 2, Blue)    | 20       | (Paper 2, Green)  |\n",
    "| (Paper 2, Green)   | 10       | -                 |\n",
    "| (Paper 2, Yellow)  | 34       | (Paper 2, Blue)   |\n",
    "| (Paper 3, Blue)    | 12       | (Paper 3, Yellow) |\n",
    "| (Paper 3, Green)   | 17       | (Paper 3, Blue)   |\n",
    "| (Paper 3, Yellow)  | 28       | -                 |\n",
    "\n",
    "We convert this to a JSON style representation where tasks are denoted by (Job,Machine) tuples in Python. The task data is stored in a Python dictionary indexed by (Job,Machine) tuples. The task data conists of a dictionary with duration ('dur') and (Job,Machine) pair for any prerequisite task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "TASKS = {\n",
    "    ('Paper_1','Blue')   : {'dur': 45},\n",
    "    ('Paper_1','Yellow') : {'dur': 10, 'prec': ('Paper_1','Blue')},\n",
    "    ('Paper_2','Blue')   : {'dur': 20, 'prec': ('Paper_2','Green')},\n",
    "    ('Paper_2','Green')  : {'dur': 10},\n",
    "    ('Paper_2','Yellow') : {'dur': 34, 'prec': ('Paper_2','Blue')},\n",
    "    ('Paper_3','Blue')   : {'dur': 12, 'prec': ('Paper_3','Yellow')},\n",
    "    ('Paper_3','Green')  : {'dur': 17, 'prec': ('Paper_3','Blue')},\n",
    "    ('Paper_3','Yellow') : {'dur': 28},   \n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Formulation\n",
    "\n",
    "Each task is represented as an ordered pair $(j,m)$ where $j$ is a job, and $m$ is a machine.\n",
    "\n",
    "| Parameter | Description |\n",
    "| :-------- | :-----------|\n",
    "| $\\text{dur}_{j,m}$ | Duration of task $(j,m)$ | \n",
    "| $\\text{prec}_{j,m}$ | A task $(k,n) = \\text{Prec}_{j,m}$ that must be completed before task $(j,m)$| \n",
    "\n",
    "| Decision Variables | Description |\n",
    "| :-------- | :-----------|\n",
    "| $\\text{makespan}$  | Completion of all jobs | \n",
    "| $\\text{start}_{j,m}$ | Start time for task $(j,m)$ |\n",
    "| $y_{j,k,m}$ | boolean variable for tasks $(i,m)$ and $(j,m)$ on machine $m$ where $j < k$ |\n",
    "\n",
    "Upper and lower bounds on the start and completion of task $(j,m)$\n",
    "\n",
    "\\begin{align}\n",
    "\\text{start}_{j,m} & \\geq 0\\\\\n",
    "\\text{start}_{j,m}+\\text{Dur}_{j,m} & \\leq \\text{makespan}\n",
    "\\end{align}\n",
    "\n",
    "Satisfying prerequisite tasks\n",
    "\n",
    "\\begin{align}\n",
    "\\text{start}_{k,n}+\\text{Dur}_{k,n}\\leq\\text{start}_{j,m}\\ \\ \\ \\ \\text{for } (k,n) =\\text{Prec}_{j,m}\n",
    "\\end{align}\n",
    "\n",
    "Disjunctive Constraints\n",
    "\n",
    "If $M$ is big enough, then satisfying\n",
    "\\begin{align}\n",
    "\\text{start}_{j,m}+\\text{Dur}_{j,m} & \\leq \\text{start}_{k,m}+M(1 - y_{j,k,m})\\\\\n",
    "\\text{start}_{k,m}+\\text{Dur}_{k,m} & \\leq \\text{start}_{j,m}+My_{j,k,m}\n",
    "\\end{align}\n",
    "\n",
    "avoids conflicts for use of the same machine. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pyomo Implementation\n",
    "\n",
    "The job shop scheduling problem is implemented below in Pyomo. The implementation consists of of a function JobShop(TASKS) that accepts a dictionary of tanks and returns a pandas dataframe containing an optimal schedule of tasks. An optional argument to JobShop allows one to specify a solver."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pyomo.environ import *\n",
    "import pandas as pd\n",
    "\n",
    "def JobShop(TASKS, solver='glpk'):\n",
    "\n",
    "    model = ConcreteModel()\n",
    "\n",
    "    JOBS = set()\n",
    "    MACHINES = set()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        JOBS.add(j)\n",
    "        MACHINES.add(m)\n",
    "        \n",
    "    BigM = 1 + sum([TASKS[(j,m)]['dur'] for (j,m) in TASKS.keys()])\n",
    "    \n",
    "    model.start = Var(JOBS, MACHINES, domain = NonNegativeReals)\n",
    "    model.makespan = Var(domain=NonNegativeReals)\n",
    "    model.y = Var(JOBS,JOBS,MACHINES, domain = Boolean)\n",
    "\n",
    "    model.Obj = Objective(expr = model.makespan, sense = minimize)\n",
    "\n",
    "    model.cons = ConstraintList()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] <= model.makespan)\n",
    "        if 'prec' in TASKS[(j,m)]:\n",
    "            (k,n) = TASKS[(j,m)]['prec']\n",
    "            model.cons.add(model.start[j,m] >= model.start[k,n] + TASKS[(k,n)]['dur'])\n",
    "        \n",
    "    for m in MACHINES:\n",
    "        for j in JOBS:\n",
    "            for k in JOBS:\n",
    "                if (j < k) and (j,m) in TASKS.keys() and (k,m) in TASKS.keys():\n",
    "                    model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] \n",
    "                                   <= model.start[k,m] + BigM*(1-model.y[j,k,m]))\n",
    "                    model.cons.add(model.start[k,m] + TASKS[(k,m)]['dur'] \n",
    "                                   <= model.start[j,m] + BigM*(model.y[j,k,m]))\n",
    "\n",
    "    # solve with indicated solver\n",
    "    SolverFactory(solver).solve(model)\n",
    "    \n",
    "    # create pandas dataframe with the optimal schedule\n",
    "    results = [[j,m,model.start[j,m](),TASKS[(j,m)]['dur'], model.start[j,m]() + TASKS[(j,m)]['dur']] \n",
    "             for (j,m) in TASKS]\n",
    "    schedule = pd.DataFrame(results,columns=['Job','Machine','Start','Duration','Finish'])\n",
    "    schedule = schedule.sort_values(by='Start')\n",
    "    schedule.set_index(['Job',\"Machine\"], inplace=True)\n",
    "    \n",
    "    return schedule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "schedule = JobShop(TASKS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Displaying a Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "JOB SCHEDULES\n",
      "\n",
      "Job: Paper_1\n",
      "         Start  Duration  Finish\n",
      "Machine                         \n",
      "Blue      42.0        45    87.0\n",
      "Yellow    87.0        10    97.0\n",
      "\n",
      "Job: Paper_2\n",
      "         Start  Duration  Finish\n",
      "Machine                         \n",
      "Green      0.0        10    10.0\n",
      "Blue      10.0        20    30.0\n",
      "Yellow    53.0        34    87.0\n",
      "\n",
      "Job: Paper_3\n",
      "         Start  Duration  Finish\n",
      "Machine                         \n",
      "Yellow     0.0        28    28.0\n",
      "Blue      30.0        12    42.0\n",
      "Green     42.0        17    59.0\n",
      "\n",
      "\n",
      "MACHINE SCHEDULES\n",
      "\n",
      "Machine: Green\n",
      "         Start  Duration  Finish\n",
      "Job                             \n",
      "Paper_2    0.0        10    10.0\n",
      "Paper_3   42.0        17    59.0\n",
      "\n",
      "Machine: Yellow\n",
      "         Start  Duration  Finish\n",
      "Job                             \n",
      "Paper_3    0.0        28    28.0\n",
      "Paper_2   53.0        34    87.0\n",
      "Paper_1   87.0        10    97.0\n",
      "\n",
      "Machine: Blue\n",
      "         Start  Duration  Finish\n",
      "Job                             \n",
      "Paper_2   10.0        20    30.0\n",
      "Paper_3   30.0        12    42.0\n",
      "Paper_1   42.0        45    87.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def Textualize(schedule):\n",
    "    \n",
    "    JOBS = list(schedule.index.get_level_values('Job').unique())\n",
    "    MACHINES = list(schedule.index.get_level_values('Machine').unique())\n",
    "\n",
    "    print('\\nJOB SCHEDULES\\n')\n",
    "    for j in sorted(JOBS):\n",
    "        print(\"Job: \" + j)\n",
    "        print(schedule.xs(j,level=0))\n",
    "        print('')\n",
    "        \n",
    "    print('\\nMACHINE SCHEDULES\\n')\n",
    "    for m in MACHINES:\n",
    "        print(\"Machine: \" + m)\n",
    "        print(schedule.xs(m,level=1))\n",
    "        print('')\n",
    "\n",
    "Textualize(schedule)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing Results with Gantt Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pqspsnVBbpwhu1qZGvLZVRJwPfH6j3Y+llD67Y1FJkiRJ6jTe977MYyf8jsac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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11f5bea20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "%matplotlib inline\n",
    "\n",
    "def Visualize(schedule):\n",
    "    \n",
    "    JOBS = list(schedule.index.get_level_values('Job').unique())\n",
    "    MACHINES = list(schedule.index.get_level_values('Machine').unique())\n",
    "    makespan = schedule['Finish'].max()\n",
    "\n",
    "    plt.figure(figsize=(12, 5 + (len(JOBS)+len(MACHINES))/4))\n",
    "    plt.subplot(2,1,1)\n",
    "\n",
    "    jdx = 0\n",
    "    for j in sorted(JOBS):\n",
    "        jdx += 1\n",
    "        mdx = 0\n",
    "        for m in MACHINES:\n",
    "            mdx += 1\n",
    "            c = mpl.cm.Dark2.colors[mdx%7]\n",
    "            if (j,m) in schedule.index:\n",
    "                plt.plot([schedule.loc[(j,m),'Start'],schedule.loc[(j,m),'Finish']],\n",
    "                     [jdx,jdx],color = c,alpha=1.0,lw=25,solid_capstyle='butt')\n",
    "                plt.text((schedule.loc[(j,m),'Start'] + schedule.loc[(j,m),'Finish'])/2.0,jdx,\n",
    "                    m, color='white', weight='bold',\n",
    "                    horizontalalignment='center', verticalalignment='center')\n",
    "    \n",
    "    plt.ylim(0.5,jdx+0.5)\n",
    "    plt.title('Job Schedule')\n",
    "    plt.gca().set_yticks(range(1,1+len(JOBS)))\n",
    "    plt.gca().set_yticklabels(sorted(JOBS))\n",
    "    plt.plot([makespan,makespan],plt.ylim(),'r--')\n",
    "    plt.text(makespan,plt.ylim()[0]-0.2,str(round(makespan,2)),\n",
    "            horizontalalignment='center', verticalalignment='top')\n",
    "    plt.xlabel('Time')\n",
    "    plt.grid()\n",
    "    \n",
    "    plt.subplot(2,1,2)\n",
    "    mdx = 0\n",
    "    for m in sorted(MACHINES):\n",
    "        mdx += 1\n",
    "        jdx = 0\n",
    "        for j in JOBS:\n",
    "            jdx += 1\n",
    "            c = mpl.cm.Dark2.colors[jdx%7]\n",
    "            if (j,m) in schedule.index:\n",
    "                plt.plot([schedule.loc[(j,m),'Start'],schedule.loc[(j,m),'Finish']],\n",
    "                     [mdx,mdx],color = c,alpha=1.0,lw=25,solid_capstyle='butt')\n",
    "                plt.text((schedule.loc[(j,m),'Start'] + schedule.loc[(j,m),'Finish'])/2.0,mdx,\n",
    "                    j, color='white', weight='bold',\n",
    "                    horizontalalignment='center', verticalalignment='center')\n",
    "\n",
    "    plt.ylim(0.5,mdx+0.5)\n",
    "    plt.title('Machine Schedule')\n",
    "    plt.gca().set_yticks(range(1,1+len(MACHINES)))\n",
    "    plt.gca().set_yticklabels(sorted(MACHINES))\n",
    "    plt.plot([makespan,makespan],plt.ylim(),'r--')\n",
    "    plt.text(makespan,plt.ylim()[0]-0.2,str(round(makespan,2)),\n",
    "            horizontalalignment='center', verticalalignment='top')\n",
    "    plt.xlabel('Time')\n",
    "    plt.grid()\n",
    "    \n",
    "    plt.tight_layout()\n",
    "\n",
    "Visualize(schedule)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Benchmark Problem LA19\n",
    "\n",
    "Lawrence 1984\n",
    "Solved in 1991"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R6TlV678KVlRUFOCb54ecH3+Laf6l1B2vpmZT4enhusRI9OmxxH9y2+lhEbePRXO4sb+0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SIohBBCCCGE8B1vvWV0gg6RDpYQQgghhBDCd3TrZnSCDpEpgkIIIYQQQgjf8f77rh8/JSNYQggh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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d8bfef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = \"\"\"\n",
    "2  44  3   5  5  58  4  97  0   9  7  84  8  77  9  96  1  58  6  89\n",
    "4  15  7  31  1  87  8  57  0  77  3  85  2  81  5  39  9  73  6  21\n",
    "9  82  6  22  4  10  3  70  1  49  0  40  8  34  2  48  7  80  5  71\n",
    "1  91  2  17  7  62  5  75  8  47  4  11  3   7  6  72  9  35  0  55\n",
    "6  71  1  90  3  75  0  64  2  94  8  15  4  12  7  67  9  20  5  50\n",
    "7  70  5  93  8  77  2  29  4  58  6  93  3  68  1  57  9   7  0  52\n",
    "6  87  1  63  4  26  5   6  2  82  3  27  7  56  8  48  9  36  0  95\n",
    "0  36  5  15  8  41  9  78  3  76  6  84  4  30  7  76  2  36  1   8\n",
    "5  88  2  81  3  13  6  82  4  54  7  13  8  29  9  40  1  78  0  75\n",
    "9  88  4  54  6  64  7  32  0  52  2   6  8  54  5  82  3   6  1  26\n",
    "\"\"\"\n",
    "\n",
    "TASKS = {}\n",
    "prec = ''\n",
    "\n",
    "lines = data.splitlines()\n",
    "job= 0\n",
    "for line in lines[1:]:\n",
    "    j = \"J{0:1d}\".format(job)\n",
    "    nums = line.split()\n",
    "    prec = ''\n",
    "    for m,dur in zip(nums[::2],nums[1::2]):\n",
    "        task = (j,'M{0:s}'.format(m))\n",
    "        if prec:\n",
    "            TASKS[task] = {'dur':int(dur), 'prec':prec}\n",
    "        else:\n",
    "            TASKS[task] = {'dur':int(dur)}\n",
    "        prec = task\n",
    "    job += 1\n",
    "    \n",
    "Visualize(JobShop(TASKS, solver='gurobi'))"
   ]
  },
  {
   "attachments": {
    "Screen%20Shot%202017-09-14%20at%209.09.57%20AM.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Application to Scheduling of Batch Processes\n",
    "\n",
    "We will now turn our attention to the application of the job shop scheduling problem to the short term scheduling of batch processes. We illustrate these techniques using an example from Dunn (2013).\n",
    "\n",
    "![Screen%20Shot%202017-09-14%20at%209.09.57%20AM.png](attachment:Screen%20Shot%202017-09-14%20at%209.09.57%20AM.png)\n",
    "\n",
    "| Process | Mixer | Reactor | Separator | Packaging |\n",
    "| :-----: | :---: | :-----: | :-------: | :-------: |\n",
    "| A       | 1.0   | 5.0     | 4.0       | 1.5       |\n",
    "| B       | -     | -       | 4.5       | 1.0       |\n",
    "| C       | -     | 3.0     | 5.0       | 1.5       |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single Product Strategies\n",
    "\n",
    "Before going further, we create a function to streamline the generation of T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Recipe(jobs,machines,durations):\n",
    "    TASKS = {}\n",
    "    for j in jobs:\n",
    "        prec = (None,None)\n",
    "        for m,d in zip(machines,durations):\n",
    "            task = (j,m)\n",
    "            if prec == (None,None):\n",
    "                TASKS.update({(j,m): {'dur': d}})\n",
    "            else:\n",
    "                TASKS.update({(j,m): {'dur': d, 'prec': prec}})\n",
    "            prec = task\n",
    "    return TASKS\n",
    "        \n",
    "RecipeA = Recipe('A',['Mixer','Reactor','Separator','Packaging'],[1,5,4,1.5])\n",
    "RecipeB = Recipe('B',['Separator','Packaging'],[4.5,1])\n",
    "RecipeC = Recipe('C',['Separator','Reactor','Packaging'],[5,3,1.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LWldE9I2IqyLiqYh4MiImFp1JrSMivpx9hj8eEVdERPeiMyk/EfH7iHgtIh5v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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1200e3cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Visualize(JobShop(RecipeA))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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423tJ0mZDBJ+TdJmke2z3zZ7rLOkN220lfaxs36clfTC7f0Ejs42R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\nAgAAAICc/H9TQK8Z8vkbmAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1231475c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Visualize(JobShop(RecipeB))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BRkbE+mN2iIgeKaWGbZpUklRIFliSJG2wusXz5havm9nwO7MDcEhKadW2DCZJ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\nrESBBQAAsBIFFgAAwEoUWAAAACv5D8GItzKAQHz6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x123134ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Visualize(JobShop(RecipeC))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overlapping Tasks\n",
    "\n",
    "Let's now consider an optimal scheduling problem where we are wish to make two batches of Product A."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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9CupYq9i5lqjmnYjtnklkWgeIiKQybzORzdoQ1bonLW97i/zPnyN373Yy/riE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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1231e2710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TASKS = Recipe(['A1','A2'],['Mixer','Reactor','Separator','Packaging'],[1,5,4,1.5])\n",
    "schedule = JobShop(TASKS,solver='gurobi')\n",
    "Visualize(schedule)\n",
    "print(schedule['Finish'].max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Earlier we found it tood 11.5 hours to produce one batch of product A.  As we see here, we can produce a second batch with only 5.0 additional hours because some of the tasks overlap.  The overlapping of tasks is the key to gaining efficiency in batch processing facilities.\n",
    "\n",
    "Let's next consider production of a single batch each of products A, B, and C."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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Tk5MMwJ6iSior6+jTtxPbP99LSIjRb0An3p+1gdKSasC3RHDMuBy6ZSUBsHlj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\nAgsAAAAACvL/AWnZmZxsfsqgAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x123284cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TASKS = RecipeA\n",
    "TASKS.update(RecipeB)\n",
    "TASKS.update(RecipeC)\n",
    "\n",
    "schedule = JobShop(TASKS,solver='gurobi')\n",
    "Visualize(schedule)\n",
    "print(schedule['Finish'].max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The individual production of A, B, and C required 11.5, 5.5, and 9.5 hours, respectively, for a total of 25.5 hours. As we see here, by scheduling the production simultaneously, we can get all three batches done in just 15 hours. \n",
    "\n",
    "As we see below, each additional set of three products takes an additionl 13 hours.  So there is considerable efficiency gained by scheduling over longer intervals whenever possible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "27.9999990802\n"
     ]
    },
    {
     "data": {
      "image/png": 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sWbP6Icwzl5GRgavEIueW+n7wUt/3r/bWPArzCpwdRq/IqABuuDGNHdvLqK1tITExBIAj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      "text/plain": [
       "<matplotlib.figure.Figure at 0x12013ba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TASKS = Recipe(['A1','A2'],['Mixer','Reactor','Separator','Packaging'],[1,5,4,1.5])\n",
    "TASKS.update(Recipe(['B1','B2'],['Separator','Packaging'],[4.5,1]))\n",
    "TASKS.update(Recipe(['C1','C2'],['Separator','Reactor','Packaging'],[5,3,1.5]))\n",
    "\n",
    "schedule = JobShop(TASKS,solver='gurobi')\n",
    "Visualize(schedule)\n",
    "print(schedule['Finish'].max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit Cleanout\n",
    "\n",
    "A common feature in batch unit operations is a requirement that equipment be cleaned prior to reuse. \n",
    "\n",
    "In most cases the time needed for clean out would be equipment and product specific. Bur for the purposes of illustration, we implement this policy with a single non-negative parameter $t_{clean} \\geq 0$ which, if specified, requires a period no less than $t_{clean}$ between the finish of one task and the start of another on every piece of equipment.\n",
    "\n",
    "This is implemented by modifying the usual disjunctive constraints to avoid machine conflicts, i.e.,\n",
    "\n",
    "\\begin{align}\n",
    "\\text{start}_{j,m}+\\text{Dur}_{j,m} & \\leq \\text{start}_{k,m}+M(1 - y_{j,k,m})\\\\\n",
    "\\text{start}_{k,m}+\\text{Dur}_{k,m} & \\leq \\text{start}_{j,m}+My_{j,k,m}\n",
    "\\end{align}\n",
    "\n",
    "to read\n",
    "\n",
    "\\begin{align}\n",
    "\\text{start}_{j,m}+\\text{Dur}_{j,m} + t_{clean} & \\leq \\text{start}_{k,m}+M(1 - y_{j,k,m})\\\\\n",
    "\\text{start}_{k,m}+\\text{Dur}_{k,m} + t_{clean} & \\leq \\text{start}_{j,m}+My_{j,k,m}\n",
    "\\end{align}\n",
    "\n",
    "for sufficiently large $M$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Makespan =  30.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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z4tmzu4LiomqGJYWROXc4kZF2vLwMefuOOu18iIh76q5toXVlPlZbJ2F//AZB\nd11C64b9BF49Dr/Zw+nMq8J3TAxWt0XzPxwjU8bPB+/YEPwuHtbbTtvmEqy2Tuzfd/xX3wTZaN9W\nRsfOI1hd3XgPDcN/wSjacw7T9n4xvmNjCfnZPLpKavAdH0/71kNYzRpxkoFr5+G1XDrqDq7N+Cmh\nAdFEBCawpeSN3u25ZasAi9mpt1DbfITlu58EwMfLlyC/cMYnXNZbtrWjgYM1u0mOnMClaXeQEjX5\nQh+OyAXhyddgrQP8eqb5AWCMucgYM8OFMXm8hoY2jh5tZNr0YXzzunFERNpZvTKf3JxyXnz+Y6qP\nNXH5gjTmzEuho72Lmp7kCuBAaS3JKRGkjIgkJ7uMDzcfpDC/itycw8QPHkR6RjwFeVWn3f+mjaUc\nPFBHekY8gwb5n7QoRWlJDYUFVSQlh/PtmyZgD7Txysvb2bf3KLPnppA2OpoP3i9h3Zqi83Z+RMS9\ntK3fT8fuCvwyU2heso3mpTvwn59G8E/m4HtRHB05h+kqqaHpr9l4xQYTeEMGbRtLeut3Haij9u63\n6T7aSPD9swi8PgO6LOjspumFrZgQP0J/vQDbxAQa//whTUuy8ZuRhP22qbRt2E/df7/jwqMXOf8K\nqz7ihS330G11s2jiI0we9nW6rK6TyryW8wi7Dq9j4bh7mZ58HUu3/4KWjka+NvZuiqq2nlT2rx/d\nR8XxIuaNuo2qxgMAtHRoASo5hYAAx83DmL4M07obY0w88CQwEWgFSoF7gBeANCAIqAZutSxr1ena\nmjRpkpWdnX1e4z1bzz27iqJ8z/mP6CerAe7bU8mLf9l65gpfMikjfbn9+5eduaB4DE1BOncNT2+i\n6ZnNrg7D7djvnE7wjzRF8Fzo9ekcy3Y90Tsa5Uyp0dMI8Y+ksa2W6cnXMjXxal7JfpiswpdOWWds\n0FXctfApp8ciruHJr1FjzDbLsr54Tu0JPHmKIJZllQPXfcEmjWKJiIiIuBm7LYxrMh4iyC+MupZK\nlu16gg2FS1wdlohTeXSCJe6htraF/7rX85bQFBERkQtre9m7bC9719VhiKf4xS8c9w895No4+siT\nr8ESEREREZGBau1ax83DKMESERERERFxEiVYIiIiIiIiTqIES0RERERExEm0yIWIiIiIiLifiAhX\nR9AvSrBERERERMT9/POfro6gX5RguaHUND99Me0AkpWV5eoQRNxO8I8ucZsv1PXkL70UOV8WjruX\nhePudXVH2NJlAAAgAElEQVQYgD5HxfPoGiwREREREXE/Dz7ouHkYjWCJiIiIiIj72bLF1RH0i0aw\nREREREREnEQJloiIiIiIiJMowRIREREREXESXYMlIiIiIiLuJyHB1RH0ixIsERERERFxP3//u6sj\n6BdNERQREREREXESJVgiIiIiIuJ+7rnHcfMwmiIoIuJGVq/M571Vha4O40tnxb+Wn3XZ+Jlb2Nd6\nfqatLBh7DwvH3Xte2hYR8Ti5ua6OoF80giUiIiIiIuIkSrBEREREREScRAmWiIiIiIiIk+gaLBER\nERERcT+pqa6OoF+UYImIiIiIiPt57jlXR9AvmiIoIiIiIiLiJBrBEhH5EhqXHsf8K0YSFh5Aa0sn\nFRUNPP+nD7Es18YVHRNE+vh49hdVU7y/2unth4UF8ODDc3sfNze1U5Bfxdv/3E1zc0ef2kqNnsZ9\nc19jfcFLvLrtYafElxo9zSntiIgMCLff7rj3sJEsjx3BMsZ0GWNyjTE7jDE5xpjpPc+PN8ZsMcbs\nMcbsNMZ8y9Wxioi4k0C7L9cvHk9nZzdvLt1F1rr9F2zfXl7mtNtjYoOZNz+V4SkR/WrfnL75XofL\n6vnHkhz2F1UzfsJgrlg4ql/7c7Yj9foONBGRXgUFjpuH8eQRrBbLssYDGGMuA34FzAKagZssyyo0\nxsQD24wxqyzLqnNhrCIibiMiwo6Pjzd1dS3s3llBa2sn72cVAzB0WCgLrxpDbFwwx+tbWbOygNzt\n5b0jPyXFNbS2dpCYFM7ePZW88epOurq6WXzzBFJSI/H19aamupmVK/LZs6uit15pSQ0dHV3ExoXw\nu8c28L3vTyUyyg5A+eF63ly6i/a2Lm68ZSIA8+anMm9+Ks8+vYXq6iau/MZYkoeH09nRzY7cclYs\ny6Orq5sHHppDkN1G9tYyMiYO5tmnt3Ck/PgZz8Hx+lZyt5dTfvg449LjGDos9JTHADBh0mAy56YQ\nER5IY/s0frNuw0nt+fsGc//c1wi3J/DEuuuJH5TKlRfdT4h/FM3t9eSWreKVbQ9jWd0MDk3j1ouf\nIiwwjqyCJVwx9i7yK7fwu3WLiBs0wpldLSIiLuCxI1ifEQLUAliWVWBZVmHPz+XAUSDKhbGJiLiV\no5UNNDa2MWp0DD9/9DLu/vFXmDJ1CAGBvnzntin4B/iwbk0htbUtLFqcQVx8SG/docNCKS6qpqjw\nGBMnJTBt+lAADh2qZ8WyPFa+kwfAohvG4+Pz6UdMYlI4ZYfqWf1uPpZlsXtnBf9+aw/r1xYRFx/C\nwqvG0NjUzsYNjkRv544jvLwkh8rKBq5fnMHoMTFsWLef/LwqZsxKZu68lN62bX4+hAzy551/76Op\nse2szoGXt8FutzFmXAwAdbWtpzyG5OHhLPp2Bt5ehn+9tYfCw7vxNt69bfl42bhzxvNEBg3l9+tv\n5FDtHhrbalmz73lez3mEvMrNzBpxI5OHfh2AW6Y+TmxICiv3PsPg0LQ+95+IiLg3Tx7BCjDG5AL+\nQBww57MFjDFTABtw4ea/iIi4uba2Lp75/WZmZiYzMi2KhCGhXLMolOMNbdjtNux2G5cv+HTKXMqI\nCHbvdIzkHDxQy4b1xYRHBDLuojiSUyLY/EEpMbFBjM+Ix8fn08QjLDyAzo5uwDEl793ljsQlJMSP\nkaOiGDosrHfKYFxcMB3tXZSW1DJjFlQeaWDH9nJsNm+Sh0dQWlLD+rX78fb2YuLkBEaOimb1yk+n\njbz+j1xaWzvP+hyMTIvmZ7+8FIC6uhZWvZvPJTMTv/AYRo12JGHL/rWXvL1HKbNt4WhrKaGBsQBM\nT74Gby9fHl+7iNKaHQAE+AYzf/SdhAbG9LY1OHQk/uXBDA0fS1HVVlbte5booETSE+adddwiIuL+\nPDnBOnGK4MXAEmPMWMtyXKJtjIkD/gbcbFlW9xc1YIy5HbgdICYmhqysrAsS+Jk0Nja6TSxy7tSf\nA8/57NPS0rMbgTkXXl6GY1VNvLl0F9AzHe+yVBKGDAIge+shcrIP95avrWk+obYjITrxWqcRI6OY\nNHkIBflVvL++mEtmJDJqTAw+Pt69Cdbx+tbe8pfMTCIxKZz3s4rJ33eUaxel4+fv+DiyTrHKxukW\n32hr6+xTcgVwoLSWVSvyaG7uoLKikeEjIk55DJ9VV1fn+Ndej+Ot1YQFxjI18SoKjm4B4LoJD2Pz\nCeC5D+4kJCCKRRMfwdfb74Tj+eIDqqurgxjYs2cPVVVVZGZm0tTUxNatW4mKimLMmDGUlpZSVVXF\n5MmTqaioIC8vj7CwMNLT03sff5npPXfgUZ8OLH3pz5TISACKPKz/PTnB6mVZ1hZjTCSOqYBHjTEh\nwDvA/7Ms68PT1HsOeA5g0qRJVmZm5oUI94yysrJwl1jk3Kk/B57z2aftrfkU5Z/fhQ5iYoO54cYM\ndmwvp7a2heTkcACOVTXR1NTOyLRoyg7W4+VlGDUmmrWrC6mtaQEcUwRnzU5maGIYAMVFn670Z7N5\nExllZ1hS2FnFERDgS9LwcELDAmhpcazg19Kzkl9icjjpGfHs2V1BcVE1w5LCyJw7nMhIO15ehrx9\nR8/pHDQ3tVNU+PlVCr/oGPbtrWTWnOEsvHI0ISH+DEm/huWFu3u355atAixmp95CbfMRlu9+EgAf\nL1+C/MIZn3BZb9nWjgYO1uwmOXICl6bdQUrU5JP2HxoaCsCYMWN6n7Pb7Sf9viUmJpKYmAhAbGws\nsbGxvds++/jLSO+5A4/6dGDpU3/2lEs4b9GcHwPiGixjTBrgDVQbY2zAW8ASy7LecG1kIiLup6Gh\njaNHG5k2fRjfvG4cEZF2Vq/MJzennBef/5jqY01cviCNOfNS6GjvoqYnuQLHyE9ySgQpIyLJyS7j\nw80HKcyvIjfnMPGDB5GeEU9BXtVp979pYykHD9SRnhHPoEH+Jy1KUVpSQ2FBFUnJ4Xz7pgnYA228\n8vJ29u09yuy5KaSNjuaD90tYt6bIqefkdMdQvL+GV1/eTne3xZXfGMPIhIvosrpOqv9aziPsOryO\nhePuZXrydSzd/gtaOhr52ti7KaraelLZv350HxXHi5g36jaqGg8A0NJx5oU5RETEM5hTTVNwd8aY\nLmDXJw+Bn1iW9Y4xZjHwIrDnhOK3WJaVe7r2Jk2aZGVnZ5+fYPtI/6kZWNSfA8/57NPVK/N5b5X7\nLdX9yWqA+/ZU8uJftp65wgAWP3ML+1r/3u/6qdHTCPGPpLGtlunJ1zI18WpeyX6YrMKXWDD2HhaO\nu9eJ0X756D134FGfDix96s/Fix33f+//e64zGWO2WZY16UzlPHaKoGVZn58Y73j+74B79IKIiMhn\n2G1hXJPxEEF+YdS1VLJs1xNsKFzi6rBERNxPWZmrI+gXj02wRETkwqmtbeG/7l3u6jAGhO1l77K9\n7F1XhyEiIufJgLgGS0RERERExB0owRIREREREXESTREUERERERH3c/HFro6gX5RgiYiIiIiI+/nV\nr1wdQb9oiqCIiIiIiIiTKMESERERERH3881vOm4eRlMERURERETE/VRXuzqCflGCJSLiRi6dP5JL\n5490dRhfKllZWWRmZvahxgLg0fMUjYiIeDpNERQREREREXESJVgiIiIiIiJOoimCIiIiIiLifubO\ndXUE/aIES0RERERE3M9DD7k6gn7RFEEREREREREnUYIlIiIiIiLu5/LLHTcPoymCIiIiIiLiflpa\nXB1Bv2gES0RERERExEk0giUiIiIibqsgr40V/1ru6jDkFOJnbmFf69/7VOeVV86u3I+PVhJhTyCy\nH3G5kkawREREREREnEQJloiIiIiIuJ1dGQFUzhzt6jD6TFMERURERETE7axZEILf2NmMcXUgfaQR\nLBERERERESdRgiUiIiIiIm7nx7+o5OLv/tHVYfSZEiwREREREREnUYIlIiIiIiLiJFrkQkRERES+\n9MalxzH/ipGEhQfQ2tJJRUUDz//pQyzLtXFFxwSRPj6e/UXVFO+vdnr7YWEBPPjw3N7HzU3tFORX\n8fY/d9Pc3NGntlKjp3Hf3NdYX/ASr2572CnxBd52t1PauZA8dgTLGNNljMk1xuwwxuQYY6afsG2l\nMabOGKNvpRMRERGR0wq0+3L94vF0dnbz5tJdZK3bf8H27eVlTrs9JjaYefNTGZ4S0a/2zemb73W4\nrJ5/LMlhf1E14ycM5oqFo/q1P2drW/euq0PoM08ewWqxLGs8gDHmMuBXwKyebb8BAoE7XBSbiIiI\niHiIiAg7Pj7e1NW1sHtnBa2tnbyfVQzA0GGhLLxqDLFxwRyvb2XNygJyt5f3jvyUFNfQ2tpBYlI4\ne/dU8sarO+nq6mbxzRNISY3E19ebmupmVq7IZ8+uit56pSU1dHR0ERsXwu8e28D3vj+VyCg7AOWH\n63lz6S7a27q48ZaJAMybn8q8+ak8+/QWqqubuPIbY0keHk5nRzc7cstZsSyPrq5uHnhoDkF2G9lb\ny8iYOJhnn97CkfLjZzwHx+tbyd1eTvnh44xLj2PosNBTHgPAhEmDyZybQmTUZVQ33cpTWTed1J6/\nbzD3z32NcHsCT6y7nvhBqVx50f2E+EfR3F5PbtkqXtn2MJbVzeDQNG69+CnCAuPIKljCFWPvIr9y\nC9vWfI253/6OM7v6gvDYEazPCAFqP3lgWdZaoMF14YiIiIiIpzha2UBjYxujRsfw80cv4+4ff4Up\nU4cQEOjLd26bgn+AD+vWFFJb28KixRnExYf01h06LJTiomqKCo8xcVIC06YPBeDQoXpWLMtj5Tt5\nACy6YTw+Pp/+6Z2YFE7ZoXpWv5uPZVns3lnBv9/aw/q1RcTFh7DwqjE0NrWzcYMj0du54wgvL8mh\nsrKB6xdnMHpMDBvW7Sc/r4oZs5KZOy+lt22bnw8hg/x559/7aGpsO6tz4OVtsNttjBkXA0Bdbesp\njyF5eDiLvp2Bt5cha+dyth1agbfx7m3Lx8vGnTOeJzJoKL9ffyOHavfQ2FbLmn3P83rOI+RVbmbW\niBuZPPTrANwy9XFiQ1JYufcZBoem9bazYV4wdWOHnH1HuglPHsEKMMbkAv5AHDCnrw0YY24HbgeI\niYkhKyvLqQH2V2Njo9vEIudO/TnwqE8HFvXnwKL+HHja2/t2HVB/tLV18czvNzMzM5mRaVEkDAnl\nmkWhHG9ow263YbfbuHzBp1PmUkZEsHunYyTn4IFaNqwvJjwikHEXxZGcEsHmD0qJiQ1ifEY8Pj6f\nJh5h4QF0dnQDjil57y53JC4hIX6MHBXF0GFhvVMG4+KC6WjvorSklhmzoPJIAzu2l2OzeZM8PILS\nkhrWr92Pt7cXEycnMHJUNKtXFvTu6/V/5NLa2nnW52BkWjQ/++WlANTVtbDq3XwumZn4hccwarQj\nCVv2r70c9HmPI/6Oq3JCA2MBmJ58Dd5evjy+dhGlNTsACPANZv7oOwkNjOlta3DoSPzLgxkaPpai\nqq2s2vcs0UGJpCfMA8C3rZvj1TUQA3v27KGqqorMzEza2trYsmUL0dHRjB49mpKSEo4dO8bkyZOp\nrKxk3759hIWFkZ6eTkVFBXl5eWd9HpzBkxOsE6cIXgwsMcaMtayzvxTRsqzngOcAJk2aZGVmZp6X\nQPsqKysLd4lFzp36c+BRnw4s6s+BRf058BTkrQLOb5Ll5WU4VtXEm0t3AT3T8S5LJWHIIACytx4i\nJ/twb/namuYTajsSohOvdRoxMopJk4dQkF/F++uLuWRGIqPGxODj492bYB2vb+0tf8nMJBKTwnk/\nq5j8fUe5dlE6fv6OP9NP9aft6f7ibWvr7FNyBXCgtJZVK/Jobu6gsqKR4SMiTnkMJwoNDeVI68lt\nHW+tJiwwlqmJV1FwdAsA1014GJtPAM99cCchAVEsmvgIvt5+JxzP5w/orl9XMeSe/TAaxowZ0/u8\nn5/fSa/zpKQkkpKSAMegSUzMp0lcbGwssbGxfToX58qTE6xelmVtMcZEAlHAUVfHIyIiIiKeIyY2\nmBtuzGDH9nJqa1tITg4H4FhVE01N7YxMi6bsYD1eXoZRY6JZu7qQ2poWwDFFcNbsZIYmhgFQXPTp\nSn82mzeRUXaGJYWdVRwBAb4kDQ8nNCyAlhZHUtnSs5JfYnI46Rnx7NldQXFRNcOSwsicO5zISDte\nXoa8fef2J3BzUztFhZ9fpfCLjmHf3kpmzRnOwitHs+PwYVJ9Y9lS8kbv9tyyVYDF7NRbqG0+wvLd\nTwLg4+VLkF844xMu6y3b2tHAwZrdJEdO4NK0O0iJmnxOx+EOBsQ1WMaYNMAbcP7alSIiIiIyoDU0\ntHH0aCPTpg/jm9eNIyLSzuqV+eTmlPPi8x9TfayJyxekMWdeCh3tXdT0JFfgGPlJTokgZUQkOdll\nfLj5IIX5VeTmHCZ+8CDSM+IpyKs67f43bSzl4IE60jPiGTTI/6RFKUpLaigsqCIpOZxv3zQBe6CN\nV17ezr69R5k9N4W00dF88H4J69YUOfWcnO4YivfX8OrL2+nutsi8aAGTh32dLqvrpPqv5TzCrsPr\nWDjuXqYnX8fS7b+gpaORr429m6KqrSeV/etH91FxvIh5o26jqvEAAC0dZ16Yw12ZPsyocyvGmC5g\n1ycPgZ9YlvVOz7aNQBoQhCPputWyrFWna2/SpElWdnb2eYz47Gl6w8Ci/hx41KcDi/pzYFF/DjzP\nPbuKovzzfx1WX32yGuC+PZW8+JetZ64wQMXP3MK+1r+fUxup0dMI8Y+ksa2W6cnXMjXxal7JfpgJ\nN/2aCHsCkVudmzz2lzFmm2VZk85UzmOnCFqW5X2abTMuZCwiIiIiItI/dlsY12Q8RJBfGHUtlSzb\n9QQbCpcwwdWB9ZPHJlgiIiIiIq5SW9vCf9273NVhDAjby95le9nnv1B4y0w76QmTiXRBTOdiQFyD\nJSIiIiIiA8uWWUGUXTnF1WH0mRIsERERERFxO/bjXdhqG10dRp8pwRIREREREbdzx1PHmHjfS64O\no8+UYImIiIiIiDiJEiwREREREREnUYIlIiIiIiLiJFqmXURERETcVmqaH7d//zJXhyGntAB49KxL\n9+nLwP98luXcjBIsERERERFxPz/4gasj6BclWCIiIiIi4n6+9S1XR9AvugZLRERERETcz6FDjpuH\n0QiWiIiIiIi4nxtvdNxnZbk0jL7SCJaIiIiIiIiTKMESERERERFxEiVYIiIiIiIiTqIES0RERERE\nxEm0yIWc1rG3HqHmX/9zXtoeFPQLrHW+56Vtd5IGVLDV1WFcEPY7pxP8o0tcHYaIyFlbvTKf91YV\nujqML5WvXjaCS+ePdHUYbmfZridYvvtJV4cBwIKx97Bw3L2uDgPuu8/VEfSLEiwREREREXE/Cxe6\nOoJ+0RRBERERERFxP/n5jpuH0QiWiIiIiIi4nzvucNzre7BERERERES+nJRgiYiIiIiIOIkSLBER\nERERESdRgiUiIiIiIuIkWuRCTitg5Mzen2O++zyDZn4XgEP/3xyGPLCOuvf+yNG/3+2q8M4L7/gQ\not5zXFRpdVt01zTTujKPhl+tA8uJO/L3IejWKXQdrqfl7T1ObFhERFxlXHoc868YSVh4AK0tnVRU\nNPD8nz7EcubnRz9ExwSRPj6e/UXVFO+vdm0w0i+p0dO4b+5rrC94iVe3PeyUNj/5vqs/f/ADcg6t\ncEqbTvXTn7o6gn7x+BEsY8xVxhjLGJPW83i8MWaLMWaPMWanMeZbro7Rk/kPTQfA+NkJnnxt7/Pt\nh/dy5E83UL/xReftzNs4ry0n6NhbSf2DK+g6VId98UT8Lk11avvG35egH15CwFVj+9eAm50vEZEv\nu0C7L9cvHk9nZzdvLt1F1rr9F2zfXl6n/0yIiQ1m3vxUhqdE9Kt9o4+cASnn0Aqe3/Qjio/luDqU\nL/bVrzpuHmYgjGBdD3zQc/8zoBm4ybKsQmNMPLDNGLPKsqw6VwbpqbyDwglIy8Q3Kgl8fOmoKcM3\nPAHb4NHE/eAf1L33R6rrK0h8dBft5fs49OgMom98mkGz76Dssbm05L9P2Nf+m9DM2/AOiqSlaAtH\nl9xJR1UJ9itmEPT0DJrf3IVt8hDa1hXR8Nh6Vx9yr66jjbQu2wuWhS1jMD4JobQH2Qh+YA5+s5Ix\nXobWNYU0PLYeq6WD4AdmE7BgNCbIRldlI03/9zEtr+8AwPaVRIL/YwY+yRF01zZTd99yQn+7wLFt\nylBi9/4njX/cRONzHxH845n4X56G8fehPfsQx3+5lu6KBgY9ejkBV4+l+dVc/GYPp+mFrTT/bZsr\nT5GIiJwgIsKOj483dXUt7N5ZQWtrJ+9nFQMwdFgoC68aQ2xcMMfrW1mzsoDc7eWEhQXw4MNzKSmu\nobW1g8SkcPbuqeSNV3fS1dXN4psnkJIaia+vNzXVzaxckc+eXRW99UpLaujo6CI2LoTfPbaB731/\nKpFRdgDKD9fz5tJdtLd1ceMtEwGYNz+VefNTefbpLVRXN3HlN8aSPDyczo5uduSWs2JZHl1d3Tzw\n0ByC7Dayt5aRMXEwzz69hSPlx112br8MYkOG9/48NfFq5o++k0j7UGqby3kq66aTyvr7BnP/3NcI\ntyfwxLrriR+UypUX3U+IfxTN7fXklq3ilW0PY1ndDA5N49aLnyIsMI6sgiVcMfYu8iu38Lt1i5gw\n5IqTRrD+fP0BKhtK6OhqvdCH/8Vycx3348e7No4+8ugRLGNMEPAV4FZgEYBlWQWWZRX2/FwOHAWi\nXBakh+uoKWPQzO8waMYtNOb8i+7mz+epXXVHOPryvQSMmE7Md//CoNl3UPfe07Tkv0/IJTcRde3/\n0lL8MTUrHsNvyDjifvjaSfX9pifS9H8f07bhwv2n72wYHy+8IgKxTR4CQMfuCoIfnEPAwtG0vL2H\n5jd2EfDNcQTddQkAncU1NDy1kYbfZNFd3UzIT7+KV1ww3sNCCfvD1XhFB9Hw2w00L90J3oaGJzc6\n6u0/Rt19y2hdVUDQHdOw3zyJ9k2lNP3lI/xmDSf01187KS7fiYNp/MMmOnaUX9gTIiIip3W0soHG\nxjZGjY7h549ext0//gpTpg4hINCX79w2Bf8AH9atKaS2toVFizOIiw/prTt0WCjFRdUUFR5j4qQE\npk0fCsChQ/WsWJbHynfyAFh0w3h8fD798y0xKZyyQ/Wsfjcfy7LYvbOCf7+1h/Vri4iLD2HhVWNo\nbGpn4wZHordzxxFeXpJDZWUD1y/OYPSYGDas209+XhUzZiUzd15Kb9s2Px9CBvnzzr/30dTYdiFO\n4ZdaRsJ8fLz8GBE1le9e/CRexpvXcn7GtkMr8DbeveV8vGzcOeN5IoOG8vv1N3Kodg+NbbWs2fc8\nr+c8Ql7lZmaNuJHJQ78OwC1THyc2JIWVe59hcGjaGeOICU6itaPpvB1nn9xzj+PmYTx9BOtKYKVl\nWQXGmGpjzETLsnr/pW+MmQLYgC/8y90YcztwO0BMTAxZbvIlZo2NjS6Nxd/fn2nTplFdXU3j9vcY\nMmsRXr7+VP/2cqIW/eYL6zRs/hvBk7/JoJnfob2ikGNv/AQA+3hHchAy9Vsw1TFb0yc0Di97GG2t\nrQQBTS98OtLjTvy+kkT0xh8C0PRSNu0fHST08YUYX2+Cbp3SW852cSIA3gmDCLwhA69AW+82n+ER\n+AwJw/j50PTshzT//+zdd5xU1f3/8ddne2cbLGWBpS4gXYqI4iKioBKDikFji8boV43RJCYm38QS\nNf5SjCXqNzHGGqNRY8OCirKAgvQunV162wbb6/n9McOyIODuOsvMLO/n43EfM3Pvufd+Zs7cmfnM\nOffcV5bWL6tJLACgLr+Mig89X5yRYybiauvYf+/HUF1LZFZPwoemYzHh9euVPDqHypmBlYwetCU3\nl7zsan+H0eL8fYyKb6k+W5em1mduru8Sh8rKWp56fC5jsrqT2act6Z0TuXRqIgeKK4mNjSA2NoKJ\nF/atL9+zVwqrVuwGYOuWQmbN3ExySgwDBnage88U5n6eS1r7OAYP6UhY2KEf2EnJ0dRU1wGwY/t+\nPnzP8x2SkBBJZt+2dOmaVN9lsEOHeKqrasnNKeTMs2DPrmKWL91JREQo3XukkJtTwMxPNxEaGsKp\nw9PJ7NuOj6evr9/Xa/9eRkVFjc9eI4Dc3Fyys3c1unwwH6MHf1M1VFlZycqVK0lPT6ddu3aEhHgS\n5rDQCFJi0xnYaRwAry99gFU7P6tfLzGmPQCnd7+U0JBwHv50KrkFnt9P0eHxTOh3M4kxafXlOyVm\nErUzni7J/dm4byEfrfkb7eIyGJQ+/rgxF5Xt4cMvX2Jcjxj69etHTk4OeXl5DB8+nD179rBmzRqS\nkpIYNGgQu3fvZu3atU16TZpSn4OLPH/sLwuy+g/2BOty4DHv/Ve9jxcDmFkH4CXgGudc3dFWds49\nDTwNMGzYMJeVldXS8TZKdnY2gRBLSkoKlO+Culqq87dRtvqTYxe2EEITPA2FIdEJWEQMrqq8fvGu\nv11J7YG99WVdVRmRUVGApyteIKpavpOyFxYR99MxxFwxhPK3VwFQu6+E/XcdOhHUVdUQ2i2ZuB+O\npHrNHooem0PU+N7EXDIQizzOIdaYM56dw47oVx+orxdA14wM+meN9ncYLS5QjlHxDdVn69LU+qyq\nWMfGdRt8su+QECNvXylvvr4S8HbHO6836Z3bALBo4TaWLNpRX76woKzB2p7P+obnOvXKbMuw4Z1Z\nv24fs2duZvSZGfQ9JY2wsND6BOvA/kNduUaP6UZGt2RmZ29m3Zq9TJk6iMgoz/eQO8Z3zvG+iior\na3yeXAFkZGSQlZXZ6PKt7RiNjIxk2LBhR10WHhr5jesfqMgnKaY9IzO+y/q98wC4bOjdRIRF8/Tn\nN5MQ3Zapp9532LaOVf9HU1pVREZGBv369QOgW7dudOvWDfA0SKSlHUri2rdvT/v27Ru9bWhifSYm\nAr3haGwAACAASURBVARd/QdtgmVmycDZwAAzc0Ao4MzsTiAeeB/4X+fcl34MM+i5mip2//OHuIri\n434KJ038GdE9TiP/nftJvuCXpF39JLuemkrpsveJH34pCaOvpnj+fwhv143ozLPY/tBxkrUAUVdY\nTsX0dbjKGpKevJi4H4+mYtYmYiYPIHJsD2rW7iP8lDRcnaPs356WKYsMI7R9ApGjutZvp3JuDq6y\nhtibPP9gWVwEVYu3U71iF662jtAuSURd2JeqJTuonL2Z8P7tSbhnPLU5BYQP7kjVwm24stbfKiQi\nEuzS2sdzxVVDWL50J4WF5XTvngxA3r5SSkuryOzTju1b9xMSYvQ9pR2ffryBwgLPn5FduiZy1tju\ndMlIAmDzxkMj/UVEhJLaNpau3ZIaFUd0dDjdeiSTmBRNebnn+6Pc+z2S0T2ZQUM6snrVbjZvzKdr\ntySyxvUgNTWWkBBj7Zq9Pns9pHlW7PiUc/veyJQhvyExuh0pMenMy3mjfvmy7R8BjrG9r6WwbBfv\nrXoUgLCQcOIikxmcfl592YrqYrYWrKJ76lDO7XMjPdsOP9FP56QUzOdgXQq85Jzr6pzLcM51BnKA\nM4G3gBedc28cdwvSKCULXqN0xYfHXB7RoQ8pk++lZOk08t+6l4L3HiJ+xBTihk/hwBcvsu+1uwhP\n60m7a54kfuRUytfPOYHRf3uVMzdRvWo3kVk9KXtxMWWvLydqQh/if3024QM7UL1kB7U5BZQ+v4iQ\n9vHEXDGEyjk59evXbimi8La3qdtbQvzPzyLm8iFQ66CmjtJnF2IJkST+8UIiTk2n5O9fUvriIiLP\n7EbsDSOpnLWJol++78dnLyIijVVcXMnevSWcdnpXLrlsACmpsXw8fR3LluzkuX8sID+vlIkX9uHs\n8T2prqqloOBQT48tuYV075lCz16pLFm0nS/nbmXDun0sW7KDjp3aMGhIR9av3Xfc/X8xJ5etW4oY\nNKQjbdpEHTYoRW5OARvW76Nb92S+f/VQYmMieOXlpaz5ai9jx/WkT792fD47h88+2dhir480zoZ9\n83l23u3UuTqmnnofw7t+h1pXe1iZ/yy5j5U7PmPSgDs4vftlvL70fsqrS7ig/21s3LfwsLLPz/8Z\nuw9sZHzfG9hXsgWA8moNWNKSrClNhoHEzGYCf3DOTW8w7zbgDiAdaHhhoWudc8uOt71hw4a5RYsW\ntUisTRVITeF5b91HwTu/a5Ftt4m7H/dZ+DcXlKARe/PpxN+qLoISXFSfrUtT6/Pj6euY8ZFvugg2\nx8HRANes3sNzzyz85hVagXPO68W5E07eLoLHMm3lI/WtUb7Uu91pJESlUlJZyOndpzAyYzKvLLqb\n7A0vHHOdg9fHaglNqs+5cz23p5/eIrE0lZktds4dvX9nA0HbRdA5N/Yo8x4HHvdDOCIiIiIiASc2\nIolLh/yWuMgkisr3MG3lI8za8KK/w2qcAEmsmipoEywRERGRYFdYWM4v7njP32FIK7Z0+4cs3X7s\nUz0CWoC1YDWWEiwREREREQk8v/Zc9ocgG6Y9mAe5EBERERERCShKsERERERERHxECZaIiIiIiIiP\nKMESERERERHxEQ1yISIiIiIigedR318X7ERQgiXHlTr5HlIn3+PvMILayXKBRBGRYHTuhMwmXfRW\npKVMGnBHi13cN2gNHuzvCJpFXQRFRERERCTwzJjhmYKMWrBERERERCTwPPCA5/acc/wbRxOpBUtE\nRERERMRHlGCJiIiIiIj4iBIsERERERERH1GCJSIiIiIi4iMa5EJERERERALP3//u7wiaRQmWiIiI\niIgEnszgvEadugiKiIiIiEjgmTbNMwUZtWAFoPilL7D++XEtsu3ki+4mdfI9LbJtkaYofuILSp+a\n6+8wmqUPsJuF/g4j4MTefDrxt472dxgB5ePp65jx0QZ/h3FS6ZkZTlaWv6MQf5m28hHeW/Wov8MA\n4ML+tzNpwB3+DiO4Pfyw53bSJP/G0URqwRIREREREfERJVgiIiIiIiI+ogRLRERERETER5RgiYiI\niIiI+IgGuRARERERkcDz0kv+jqBZlGCJiIiIiEjg6dzZ3xE0i7oIioiIiIhI4PnPfzxTkFELVgBq\nP3ISpctfBCDtun/QZsx1AGz7f2fT+a7PKJrxJHv/dZs/QxRptUI7JtB2xo0AuDpHXUEZFdPXUvzQ\nZ+B8uKOoMOKuH0Htjv2Uv73ahxuW1mzAoA5MOD+TpORoKspr2L27mH/835c4X743m6FdWhyDBndk\n08Z8Nm/K928w0upERUX5bFu9253Gz8b9h5nrX+DVxXf7ZJsHr3f198//hyXbPvDJNsXr//7Pc/u9\n7/k3jiYK+hYsM/uumTkz69Ng3nQzKzKz9/wZW3Ol9jsDAIuMJX74lPr5VTu+Ytf/XcH+Oc/5KzSR\nk0b1V3vY/6sPqN1WROyVpxJ5bm+fbt+iwom7ZTTR3+3fvA2Emk/jkcAXExvO5VcOpqamjjdfX0n2\nZ5tO2L5DQo7/fktrH8/4Cb3p0TOlWds3vZ0liC3Z9gH/+OJWNuct8XcoEiBaQwvW5cDn3tt7vPP+\nBMQAN/orqG8jMrEd0X2yCG/bDcLCqS7YTnhyOhGd+tHhf/5N0Ywnyd+/m4wHV1K1cw3bHjyTdlc9\nQZuxN7L9D+MoXzebpAt+SWLWDYTGpVK+cR57X7yZ6n05xPQ5y99PTyQo1O4toWLaV+AcEUM6EZae\nSFVcBPF3nU3kWd2xEKPikw0U/2Emrrya+LvGEn1hPywugto9JZT+cwHlry0HIOKMDOJ/ciZh3VOo\nKyyj6GfvkfjnCz3LRnSh/Vd3UvLkF5Q8PZ/4n44hamIfLCqMqkXbOPDAp9TtLqbNgxOJntyfsleX\nETm2B6XPLqTspcX+fInkBEtJiSUsLJSionJWrdhNRUUNs7M3A9ClayKTvnsK7TvEc2B/BZ9MX8+y\npTtJSormV3ePI2dzARUV1WR0S+ar1Xt449UV1NbWceU1Q+nZO5Xw8FAK8suY/sE6Vq/cXb9ebk4B\n1dW1tO+QwF/+MIsf3jSS1LaxAOzcsZ83X19JVWUtV117KgDjJ/Rm/ITe/O2JeeTnl3LRxf3p3iOZ\nmuo6li/byQfT1lJbW8ddvz2buNgIFi3czpBTO/G3J+axa+cBv7220nq0T+hRf39kxmQm9LuZ1Ngu\nFJbt5LHsqw8rGxUez8/H/Yfk2HQe+exyOrbpzUUDf05CVFvKqvazbPtHvLL4bpyro1NiH64f9RhJ\nMR3IXv8i5/f/Mev2zOMvn01laOfzD2vB+vvlW9hTnEN1bcWJfvoSIIK6BcvM4oAzgOuBqQfnO+c+\nBYr9Fde3VbJrE23G/IA2Z15LyZJ3qCsr+lqZ2qJd7H35DqJ7nU7adc/QZuyNFM14gvJ1s0kYfTVt\np/ye8s0LKPjgD0R2HkCHW4Kv/6qIP1lYCCEpMUQM95xgW71qN/G/OpvoSf0of3s1ZW+sJPqSAcT9\neDQANZsLKH5sDsV/yqYuv4yE35xDSId4QrsmkvTXyYS0i6P4z7Moe30FhBrFj87xrLcpj6KfTaPi\no/XE3XgasdcMo+qLXEqfmU/kWT1I/OMFh8UVfmonSv76BdXLd57YF0T8bu+eYkpKKunbL417HzyP\n2356BiNGdiY6Jpwf3DCCqOgwPvtkA4WF5Uy9cggdOibUr9ulayKbN+azcUMepw5L57TTuwCwbdt+\nPpi2lunvrwVg6hWDCQs79NMgo1sy27ft5+MP1+GcY9WK3bz71mpmfrqRDh0TmPTdUygprWLOLE+i\nt2L5Ll5+cQl79hRz+ZVD6HdKGrM+28S6tfs486zujBvfs37bEZFhJLSJ4v1311BaUnkiXkI5CQxJ\nn0BYSCS92o7kulGPEmKh/GfJPSze9gGhFlpfLiwkgpvP/AepcV14fOZVbCtcTUllIZ+s+QevLbmP\ntXvmclavqxje5TsAXDvyYdon9GT6V0/RKbHPsXZfLy2+GxXVpS32PCWwBXsL1kXAdOfcejPLN7NT\nnXON/kvXzH4E/AggLS2N7OzsFgrzm0VFRXHaaaeRn59P0fKZdBt3JSHhUeT/eSJtp/7pqOsUz32J\n+OGX0GbMD6javYG8N34NQOxgzw+yhJHfg5GePqthiR0IiU2iqKiIGGDDhg3s2LHjhDy3k11JSYlf\n31uBKjV3B6n+DuI4Is/oRrs5twBQ+sIiquZvJfHhSVh4KHHXj6gvFzEqA4DQ9DbEXDGEkJiI+mVh\nPVII65yERYZR+rcvKXtlaf2ymsQCAOryy6j40PPjNnLMRFxtHfvv/Riqa4nM6kn40HQsJrx+vZJH\n51A588R1DWuKLbm55GVX+zuMJmvJYzQ313eJQ2VlLU89PpcxWd3J7NOW9M6JXDo1kQPFlcTGRhAb\nG8HEC/vWl+/ZK4VVK3YDsHVLIbNmbiY5JYYBAzvQvWcKcz/PJa19HIOHdCQs7NAPz6TkaGqq6wDY\nsX0/H77neX8mJESS2bctXbom1XcZ7NAhnuqqWnJzCjnzLNizq5jlS3cSERFK9x4p5OYUMPPTTYSG\nhnDq8HQy+7bj4+nr6/f12r+XUVFR47PXCKCqqlqfua1MbW3t1+ZVVlaycuVK0tPTadeuHSEhnj8G\nwkIjSIlNZ2CncQC8vvQBVu38rH69xJj2AJze/VJCQ8J5+NOp5BZ4ehtEh8czod/NJMak1ZfvlJhJ\n1M54uiT3Z+O+hXy05m+0i8tgUPr448ZcVLaHD798iXE9YujXrx85OTnk5eUxfPhw9uzZw5o1a0hK\nSmLQoEHs3r2btWvXfrsXKYg05TN3cJGnkWFZkB3TwZ5gXQ485r3/qvdxoxMs59zTwNMAw4YNc1lZ\nWb6Or8lSUlLYumkxjL2c6vxtlK3+5NiFLYTQhLYAhEQnYBExuKry+sW7/nYltQf21pd1VWUkJiYC\n0KtXL3r16tViz0MOyc7OJhDeW4GmeNUXlBK4rTBVy3dS9sIi4n46hpgrhlD+9ioAaveVsP+uQycx\nu6oaQrslE/fDkVSv2UPRY3OIGt+bmEsGYpHH+YhtzKgEzmFHnPtSu7ekWc/nROiakUH/rNH+DqPJ\nWvIYrapYx8Z1G3yyrZAQI29fKW++vhLwdsc7rzfpndsAsGjhNpYsOvTHWWFBWYO1Pe+jhuc69cps\ny7DhnVm/bh+zZ25m9JkZ9D0ljbCw0PoE68D+Q12cRo/pRka3ZGZnb2bdmr1MmTqIyCjPe9wd4/18\nvLd5ZWWNz5MrgIiIcH3mtjJffvnl1+ZFRkYybNiwo5YPD438xm0eqMgnKaY9IzO+y/q98wC4bOjd\nRIRF8/TnN5MQ3Zapp9532LaO9T4/mtKqIjIyMujXrx8A3bp1o1u3boDnT/20tENJXPv27Wnfvn2j\ntx3smvSZO2MGAFmpgfyX7NcFbYJlZsnA2cAAM3NAKODM7E7XlCMgANVVVbD7nz/EVRQf99spaeLP\niO5xGvnv3E/yBb8k7eon2fXUVEqXvU/88EtJGH01xfP/Q3i7bkRnnsX2h46TrInIYeoKy6mYvg5X\nWUPSkxcT9+PRVMzaRMzkAUSO7UHN2n2En5KGq3OU/dvTMmWRYYS2TyByVNf67VTOzcFV1hB702me\nMnERVC3eTvWKXbjaOkK7JBF1YV+qluygcvZmwvu3J+Ge8dTmFBA+uCNVC7fhyoKvVUh8L619PFdc\nNYTlS3dSWFhO9+7JAOTtK6W0tIrMPu3YvnU/ISFG31Pa8enHGygs8Pzp1qVrImeN7U6XjCQANm88\nNNJfREQoqW1j6dotqVFxREeH061HMolJ0ZSXe96b5d73aEb3ZAYN6cjqVbvZvDGfrt2SyBrXg9TU\nWEJCjLVr9vrs9RA5nhU7PuXcvjcyZchvSIxuR0pMOvNy3qhfvmz7R4BjbO9rKSzbxXurHgUgLCSc\nuMhkBqefV1+2orqYrQWr6J46lHP73EjPtsNP9NM5eQVZYnVQMJ+DdSnwknOuq3MuwznXGcgBzvRz\nXD5RsuA1Sld8eMzlER36kDL5XkqWTiP/rXspeO8h4kdMIW74FA588SL7XruL8LSetLvmSeJHTqV8\n/ZwTGL1I61E5cxPVq3YTmdWTshcXU/b6cqIm9CH+12cTPrAD1Ut2UJtTQOnziwhpH0/MFUOonJNT\nv37tliIKb3ubur0lxP/8LGIuHwK1DmrqKH12IZYQSeIfLyTi1HRK/v4lpS8uIvLMbsTeMJLKWZso\n+uX7fnz2EkiKiyvZu7eE007vyiWXDSAlNZaPp69j2ZKdPPePBeTnlTLxwj6cPb4n1VW1FBQc6tGw\nJbeQ7j1T6NkrlSWLtvPl3K1sWLePZUt20LFTGwYN6cj6tfuOu/8v5uSydUsRg4Z0pE2bqMMGpcjN\nKWDD+n10657M968eSmxMBK+8vJQ1X+1l7Lie9OnXjs9n5/DZJxtb7PURaWjDvvk8O+926lwdU0+9\nj+Fdv0OtO7yr4X+W3MfKHZ8xacAdnN79Ml5fej/l1SVc0P82Nu5beFjZ5+f/jN0HNjK+7w3sK9kC\nQHm1BmZpcc8/75mCjAVrY4+ZzQT+4Jyb3mDebUBfoD/QB4gD8oHrnXMfHW97w4YNc4sWLWrBiBtv\n8SM/IN57HSxfS77oblIn3/PNBcVn1EXw6Iqf+ILSp+b6OwzxodibTyf+VnURbOjj6euY8ZFvugg2\nx8HRANes3sNzzyz85hVagZ6Z4fzopvO+uaAEjaYco9NWPlLfGuVLvdudRkJUKiWVhZzefQojMybz\nyqK7yd7wwjHXOXh9LDlckz5zD5YLkHOwzGyxc+7ofVMbCNougs65sUeZ97g/YhERERGR1is2IolL\nh/yWuMgkisr3MG3lI8za0DJ/hkvwC9oES0RERI6vsLCcX9zxnr/DEAl6S7d/yNLtxz51Q6ShYD4H\nS0REREREJKAowRIREREREfERdREUEREREZHA88EH31wmACnBEhERERGRwBMT4+8ImkVdBEVERERE\nJPA89ZRnCjJKsEREREREJPC89ppnCjLqIhiAiodcw6l3POfvMERaVPyto4PyorSgi0dL4507IZNz\nJ2T6O4yTSnaAXJBU/GPSgDt0cV/xO7VgiYiIiIiI+IgSLBERERERER9RgiUiIiIiIuIj5pzzdwwB\nwcz2AVv8HYdXKpDn7yDEZ1SfrY/qtHVRfbYuqs/WR3XaugRzfXZ1zrX9pkJKsAKQmS1yzg3zdxzi\nG6rP1kd12rqoPlsX1WfrozptXU6G+lQXQRERERERER9RgiUiIiIiIuIjSrAC09P+DkB8SvXZ+qhO\nWxfVZ+ui+mx9VKetS6uvT52DJSIiIiIi4iNqwRIREREREfERJVgiIiIiIiI+ogQrwJjZBDNbZ2Yb\nzewuf8cj346Z5ZrZSjNbZmaL/B2PNJ2ZPWtme81sVYN5yWb2iZlt8N4m+TNGabxj1Oe9ZrbDe5wu\nM7Pz/RmjNJ6ZdTazmWb2lZmtNrOfeOfrGA1Cx6lPHaNByMyizGyBmS331ud93vnJZvapmVWYWbGZ\nrTli2Tceu4H++0rnYAUQMwsF1gPjge3AQuBy59xXfg1Mms3McoFhzrlgvaDeSc/MxgAlwIvOuf7e\neX8ECpxz/8/7R0iSc+6X/oxTGucY9XkvUOKc+7M/Y5OmM7MOQAfn3BIziwcWA98FrkXHaNA5Tn1e\nho7RoGNmBsQ650rMLBz4HPgJcDFQADwB3AqkAGMaLvumYzfQf1+pBSuwjAA2Ouc2O+eqgFeBi/wc\nk8hJzTk3G88XQUMXAS9477+A5weABIFj1KcEKefcLufcEu/9YmAN0Akdo0HpOPUpQch5lHgfhnsn\nh/f49C57wfv4sGXedYL22FWCFVg6AdsaPN6OPliCnQNmmNliM/uRv4MRn0lzzu3y3t8NpPkzGPGJ\nH5vZCm8XQnUnC0JmlgEMAeajYzToHVGfoGM0KJlZqJktA/YCnzjn6o9Pb8+tD4FeRy7zrn68Yzeg\nf18pwRJpWWc45wYDE4FbvN2TpBVxnn7W6msd3P4P6A4MBnYBD/s3HGkqM4sD/gvc7pw70HCZjtHg\nc5T61DEapJxztd7fQenACDPrf5Rl+49c5l1+vGM3oH9fKcEKLDuAzg0ep3vnSZByzu3w3u4F3sLT\nDVSC3x7vuQIHzxnY6+d45Ftwzu3xftHXAf9Ax2lQ8Z7b8V/gZefcm97ZOkaD1NHqU8do8HPOFQEz\ngQl8/fjcc5xlRz12A/33lRKswLIQ6GVm3cwsApgKvOvnmKSZzCzWe5IuZhYLnAusOv5aEiTeBa7x\n3r8GeMePsci3dPDL3GsyOk6Dhvck+n8Ca5xzf2mwSMdoEDpWfeoYDU5m1tbMEr33o/EM4rYWz/F5\ns3fZNcD7Ryw77rEbDL+vNIpggPEOPfooEAo865x70M8hSTOZWXc8/6oAhAH/Vn0GHzN7BcgCUvH8\ny3YP8DbwGtAF2AJc5pzTwAlB4Bj1mYWn65EDcoEbG5wDIAHMzM4A5gArgTrv7F/jOW9Hx2iQOU59\nXo6O0aBjZgPxDFQRiqdR5zXn3O/MLAX4ABgEVOMZc+CVBsu+duyaWUfgGefc+cHw+0oJloiIiIiI\niI+oi6CIiIiIiIiPKMESERERERHxESVYIiIiIiIiPqIES0RERERExEeUYImIiIiIiPhImL8DEBER\naWneoX8/9T5sD9QC+7yPy5xzp/slMBERaXU0TLuIiJxUzOxeoMQ592d/xyIiIq2PugiKiMhJzcxK\nvLdZZjbLzN4xs81m9v/M7PtmtsDMVppZD2+5tmb2XzNb6J1G+/cZiIhIIFGCJSIicsgg4CagL3AV\n0Ns5NwJ4Bvixt8xjwCPOueHAJd5lIiIigM7BEhERaWihc24XgJltAj72zl8JjPXePwfoZ2YH10kw\nszjnXMkJjVRERAKSEiwREZFDKhvcr2vwuI5D35khwGnOuYoTGZiIiAQHdREUERFpmo851F0QMxvs\nx1hERCTAKMESERFpmtuAYWa2wsy+wnPOloiICKBh2kVERERERHxGLVgiIiIiIiI+ogRLRERERETE\nR5RgiYiIiIiI+IgSLBERERERER9RgiUiIiIiIuIjSrBERERERER8RAmWiIiIiIiIjyjBEhERERER\n8RElWCIiIiIiIj6iBEtERERERMRHlGCJiIiIiIj4iBIsERERERERH1GCJSIiAc3MnjezB46zvMTM\nup/ImI7HzLLN7Ic+2ta9ZvYvX5cVEZGWowRLRES+FTPLNbMqM0s9Yv5SM3NmltGS+3fOxTnnNvt6\nu2Z2ipl9bGYFZlZkZovN7Hxf70dERFoXJVgiIuILOcDlBx+Y2QAgxn/h+MQ04BOgPdAOuA044NeI\nREQk4CnBEhERX3gJuLrB42uAFxsWMLMLvK1aB8xsm5nde8TyM8xsrre1aJuZXdtgcZKZvW9mxWY2\n38x6NFjPmVlP7/3nzezJ45TtY2afeFul1pnZZUd7Mt7WuG7AP5xzVd7pC+fc5w3KXGRmy7zPZ5OZ\nTWiwia5m9oU3ho8btu6Z2WkNnudyM8tqsKybmc3yrvcJ0HC9LDPbfkScuWZ2zjGewzH3IyIiLUcJ\nloiI+MKXQIKZ9TWzUGAqcOT5QKV4krBE4ALgf8zsuwBm1hX4EPgr0BYYDCxrsO5U4D4gCdgIPHic\nWI5a1sxi8bRI/RtPi9RU4Ckz63eUbeR71/2XmX3XzNIaLjSzEXgSyDu9z2cMkNugyBXAD7z7iQB+\n7l2vE/A+8ACQ7J3/XzNr613v38BiPInV/XgS1SZrxH5ERKSFKMESERFfOdiKNR5YA+xouNA5l+2c\nW+mcq3POrQBeAc7yLr4CmOGce8U5V+2cy3fONUyw3nLOLXDO1QAv40nAjuVYZS8Ecp1zzznnapxz\nS4H/AlOO3IBzzgFj8SRNDwO7zGy2mfXyFrkeeNY594n3+exwzq1tsInnnHPrnXPlwGsNYrgS+MA5\n94F3vU+ARcD5ZtYFGA781jlX6ZybjaebYnMccz/N3J6IiDSSEiwREfGVl/AkStdyRPdAADMbaWYz\nzWyfme0HbuJQF7jOwKbjbHt3g/tlQFwzynYFRnq7zBWZWRHwfTznWH2Nc267c+5W51wP77qlDZ5X\nc+PtCkw5IoYzgA5AR6DQOVfaYN0tx9nH8RxvPyIi0oLC/B2AiIi0Ds65LWaWg6eV5PqjFPk38AQw\n0TlXYWaPcijB2gaMaOEQtwGznHPjm7qic26bmT2Jp9Xt4LZ6HGeV48XwknPuhiMXeLtJJplZbIMk\nqwvgvPdLaTBwiLcr5rG6/B1zPyIi0rLUgiUiIr50PXD2Ea0wB8UDBd7kagSe1q6DXgbOMbPLzCzM\nzFLM7HjdAJvjPaC3mV1lZuHeabiZ9T2yoJklmdl9ZtbTzEK8g1Rch+dcM4B/Aj8ws3He5Z3MrE8j\nYvgXMMnMzjOzUDOL8g5eke6c24KnG999ZhZhZmcAkxqsux6I8g4WEg78Bohs6n4a80KJiEjzKcES\nERGfcc5tcs4tOsbim4HfmVkxcDeec5MOrrcVT8vXz4ACPANcDPJxbMXAuXgGt9iJpxvfHzh6klIF\nZAAz8AzNvgqoxNP9EefcAjyDWDwC7Adm4emW900xbAMuAn4N7MPT0nQnh76PrwBG4nkN7qFBV0vn\n3H48r+EzeM5vKwUOG1WwCfsREZEWYp7zeEVEREREROTb0j9ZIiIiIiIiPqIES0RERERExEeUYImI\niIiIiPiIEiwREREREREf0XWwvFJTU11GRoa/wwCgtLSU2NhYf4chPqL6bH1Up62L6rN1UX22PqrT\n1qVJ9VlS4rmNO9615U+cxYsX5znnjnX9wXpKsLwyMjJYtOhYIwufWNnZ2WRlZfk7DPER1Wfrozpt\nXVSfrYvqs/VRnbYuwVyfZralMeXURVBERERERALP3LmeKcioBUtERERERALPr3/tuc3O9msYuFob\nBAAAIABJREFUTaUWLBERERERER9RgiUiIiIiIuIjSrBERERERER8RAmWiIiIiIiIj2iQCxERERER\nCTyPPurvCJpFCZaIiIiIiASewYP9HUGzqIugiIiIiIgEnhkzPFOQUQuWiIiIiIgEngce8Nyec45/\n42gitWCJiIiIiIj4iBIsERERERERH1EXwQC0fm0lH7zznr/DEB/pmRlOVlbjy09b+QjvrQrOUXNO\nJq+80rhyF/a/nUkD7mj0dotX30fJmt81Myppjkxg1xuNLx/X927iT7mnUWXz3rqPgndUnydS/KCr\nacqHbvETX1D61NyWC0i+Jvbm04m/dXSjyxdveJNXPry6BSOSb6P/ObczYPxP/R1GQFELloiIiIiI\niI+oBUtERERERALP3//u7wiaRQmWiIiIiIgEnsxMf0fQLOoiKCIiIiIigWfaNM8UZNSCJSIiIiIi\ngefhhz23kyb5N44mUguWiIiIiIiIjyjBEhERERER8RF1EZQTIiIilPPOz2TAoA7ExkZQVFjOnFmb\nKSwo5/xJfUlrH09IiHHvbz6irLTa3+GKj0WGxXDRwJ8ztPP5xEUmUVC6kxnrnqFjm0wGdDybNtFt\nKSjdyXurHmPBlrf9Ha40Q2hMV9qdvxkA5+qoq8qnas8M9i++kdhePyG669WExqRTV7mP0g2PUbpB\n13oLJG3G/Q9pVz0BQM5dfanevR4Lj6LTHe8S1X0kIVFx7Hv1Tgqn/8XPkZ6cYi4fQsJvzwFg3/nP\nUJtbSOTYHsTdMprQrklQVUPFzE0cuH8GVNb4OVo5KDYpne/c5bnGmquro7KskN0b5rDwzbuIb9uD\n4Rc/RFKHfoSEhvHR4xdSsGOFnyMWX2lSC5aZ/a+ZrTazFWa2zMxGtlRgx4kh0cxuPtH7lW/nBzeM\n4MyzurN3TwnvvLmaFct3kd45kfCIUHI2F1CQX+bvEKUF3TLmWcZlXs+u/Rt4dfE9LN72AV2TB5GR\nPJAvc/7L60seIDoigWtPe5jU2M7+Dle+herCJRQtuIrqvM+J7nI5MT1uIjx5BBU732H/sttxdVUk\nDHqYiNQx/g5VGogfcRmurtZ7f4pnZkgotaWFlK78yI+RCUDUxExcbZ3n/oQ+AIRltqNmUz7Ff5hJ\n9eo9xFw8gNjrR/gzTDmGgh0rmffqbezLXUDGkO/S87SrCA2Pomjnagp3rvZ3eNICGt2CZWajgAuB\noc65SjNLBSJaIigzC3POHesvmETgZuApH21PWljPXin06JnC7t3F/PPv83HOM98MnINVK3Zz4y2j\nSG0b699ApUX0SRtNZtoodu5fz+PZV+PwvAEMIyQkjNo6T4tl2/iujO9zA+0TepJXus2fIcu3UFeZ\nR9WeGYTGdCWq02QsPIHCeVPAeerZQiJpM+RxwhL6UZU328/RCkBoYgeie42meMHrxGSeSfyIyyh4\n90FcZSm7nvweCWdcQ/zwS/wd5kkrpG0s4UM6UTF9HRHD0omamEnp3+ZR+s/5UO1JuqqX7yTyjG6E\n9Uzxc7RyNJWlBeze+DmxSZ3p3H8i4VFx5OUuJC93ISOnPExK50H+DjFwvfSSvyNolqZ0EewA5Dnn\nKgGcc3kAZnYq8BcgDsgDrnXO7TKzbGA5cJZ3P9c55xaY2QjgMSAKKAd+4JxbZ2bXAhd7txNqZhcA\n7wBJQDjwG+fcO8D/A3qY2TLgE+AXwB+BiYADHnDO/cfMsoD7gUKgD9C76S+P+EKnzokAbFi3rz65\nAg67L61Xl+T+AKzZPac+uQJwuPrkKsTCyGw3isqaMrYUrvRLnOIbke3PJe07ewCoLd9B2cYn65Mr\ngMi0c3Gulqr8uf4KUY4QP/xSLCSUkoVvUFuSR9I5txLRsS9VO9f4OzQBos7LxEJDqPhoHXVF5cR+\nfyihPVKo3ZRfXybijG4AVC/a7q8w5Tg69D6Li+9eBkDZ/t1smPuCnyMKIp2Ds1dLUxKsj4G7zWw9\nMAP4DzAX+CtwkXNun5l9D3gQuM67ToxzbrCZjQGeBfoDa4EznXM1ZnYO8Hvg4F9jQ4GBzrkCMwsD\nJjvnDnhby740s3eBu4D+zrnBAGZ2CTAYGASkAgvNbHaD7fV3zuUc7QmZ2Y+AHwGkpaWRnZ3dhJej\n5VRVtbJzkE7yTKqqqrpJ763c4twWi8UvvqH6QyyU60c9SnpSP56ddzvFFXknJq4TJDc3l+z87EaX\nTynNJbXlwmlxVflfUrz6biLankV83/8lpsdNlHz1OwDiB/6JqI4XcmDlr6jZH7znGuTm5pK/L7tR\nZeNzc4lv2XC+tfgRU6irrqRq11osIgbO8XQZzH/7Pn+H1ixVVVVN+sxNzd0R0Mdc1IQ+uKoaanIK\nsOhw+D5ET+xDyRNfABA5vjfxt59JxaxNlL26zM/RNs6W3Fzyshv/W6eqqqoFo2l5eVuXsOKjP9Ou\n+2n0H3cbPU+7ilUzHvF3WD6Tm5tLfhOOuZKSkkYfo20/+wyAfWef3YzI/KfRCZZzrsTbWnUmMBZP\ngvUAnqTpEzMDCAV2NVjtFe+6s80swcwSgXjgBTPrheenV3iD8p845wq89w34vTc5qwM6AWlHCe0M\n4BXnXC2wx8xmAcOBA8CCYyVX3rieBp4GGDZsmMvKymrsy9Gi1q/9CGg9Sdb2bfsB6NU7tb5bIHDY\n/dYsIiKcpry3ilcuZdWqlovnRDvYItUn7QwMO6yLoFkoN4x+gsHp5/GvBb9i4ZZ3/Blqi8jIyCBr\nQFajyxevnkVJEDcc1FXlU7X3U6ryviC+7/8S2X4iJV/9joRBjxDb6zaKv7qf0nV/9HeY30pGRgYD\nTslqVNm8wlkULG/ZeL6NsOR0onqMwkJCyPj9oQ+euBFTgjbBioiIYFRTPnNXfUEpO1suoG8hpH08\n4YM7YiFG22nX1c+POi+Tkie+IGpCJm3+cAFV87dS9JN3oC44vlS7ZmTQP2t0o8tP2/AmwZxiVZYW\nsmfj5+TlLqT/uNvo2Gdsq0qwMjIyGNCEYy47O7vxv4vuvddz+7vfNTUsv2rSKILeJCYbyDazlcAt\nwGrn3KhjrXKUx/cDM51zk80sw7u9g0ob3P8+0BY41TlXbWa5eLoVNkXpNxeRlrZpYz6bNuTRo1cq\n190wgpXLd5GYFE1CmyiyP91E9x7JJCREAjD01HTy8kpZ+9VeP0ctvrJuz1zW7ZlHZtoofpz1PIu3\nfkhybEcSo9OICItmaOeJrNjxKZU1pQzrMomc/GXk6xysoBUa1YGo9O8RkXoGALWlW4jv/yCxvW6j\nqmA+NQfWEJX+PWoOrKLmgE7u9re44ZdiISHkT3uIipyFALQZcx1xgy8kIn0AUd1HEN3T8xUf1X0E\nCWOup3j+q7hKfb2eCFHnZWIhRsnTX1K90vP/dfTFA4ga25OYK4cS/4uxuAMVVHywhqhxvagrKKNq\n/lY/Ry1Hik5oR5dBk2ib4RmEpLRwO1Hx7ejY52ziUz3dOzudMp64lK5sXTHNn6GKjzRlkItMoM45\nt8E7azCwBjjXzEY55+aZWTjQ2zl38Fvze8BMMzsD2O+c229mbYAd3uXXHmeXbYC93uRqLNDVO78Y\nDutxMQe40cxeAJKBMcCdeM67kgDx3DMLmXBBHwYM7ECPXqnsLypn1szNdO2WxKVTD53c+Z3Jp7Bp\nY74SrFbmydnXcdHAOxna+Xwyh51OYdkuPl77NOf1vQmAgZ3GMbDTOACe//JnzMtRghWswpOGknTa\nv6mr3k/F7o8oXvkL2gx/DoCI5JFEnPZvAIq/uo+Sr5Rg+Ztn9MA6ij5+lNpiT/dcC40gbvCFxI+Y\nQsp3/rdB2SnEj5hC2VczqFGCdUJETczE1TlKX1iEKywHwMJDiRrbk5DkGCwsBEuOoc3vzwegasFW\nCpRgBZzkTgMYfcWTVFUcYNe6bJa+/yAJbbsz8tJDrfn9x/2EkoJtSrBaiaa0YMUBf/V286sBNuI5\nf+lp4HFv4hQGPAoc/NasMLOleLoBHmzb/iOeLoK/Ad4/zv5eBqZ5W8oW4Tl3C+dcvpl9YWargA/x\nDHIxCs+AGg74hXNut5kpwQogVVW1vPvWat596+s/qBYv1Em5rV1lTRmvLbmP15Yc3uVo9sZ/+Ski\n8bXasi3seiP0qMsKZo07wdFIY227//SvzStZ+Drrr30dgPw37z7RIUkDBVNf/tq8iunr2D39TwCU\nPP75iQ5JmqC0cDuv/LLLUZeVFe045jIJfk05B2sx8PVPYs/Igce6oMm/nHO3H7GdeRw+ot9vvPOf\nB55vUC4PT+J0tFiuOGLWnd6pYZlsDu9+KCIiIiIi0qKadA6WiIiIiIjICfHGG/6OoFlaLMFyzmW1\n1LZFRERERKSVSw3kiygcW4i/AxAREREREfma55/3TEFGCZaIiIiIiAQeJVgiIiIiIiInNyVYIiIi\nIiIiPqIES0RERERExEfMOefvGALCsGHD3KJFi/wdBgDZ2dlkZWX5OwzxEdVn66M6bV1Un62L6rP1\nUZ22Lk2qz4PlsrNbKJqmMbPFzrlh31RO18ESEREREZHA88EH/o6gWZRgiYiIiIhI4ImJ8XcEzaJz\nsEREREREJPA89ZRnCjJKsEREREREJPC89ppnCjJKsERERERERHxECZaIiIiIiIiPKMESERERERHx\nESVYIiIiIiIiPqJh2kVEREREJPAEyAWGm0otWCIiIiIiIj6iBEtERERERALPn//smYKMEiwRERER\nEQk8773nmYKMEiwREREREREfUYIlIiIiIiLiI0qwREREREREfETDtIuIiIiISOCJjvZ3BM2iBEtE\nRERERALPhx/6O4JmURdBERERERERH1GCJSIiIiIigef++z1TkFGCJSIiIiIigefTTz1TkFGCJSIi\nIiIi4iNKsERERERERHxECZaIiIiIiIiPaJh2EREREREJPCkp/o6gWZRgiYiIiIhI4Pnvf/0dQbOo\ni6CIiIiIiIiPqAVL/Kb4iS8ofWquv8NocX2A3Sz0dxgnROzNpxN/6+hGlc176z4K3vldC0fUMjoC\n65/3dxSBJ/miu0mdfE+jyn48fR0zPtrQwhE13gfvvOfvEAA457xenDshs9Hlp618hPdWPdqCEQWf\n/nHfJYssf4chIr7wq195bh96yL9xNJESLBERERERCTzz5vk7gmZRF0EREREREREfUYIlIiIiIiLi\nI0qwREREREREfETnYImIiIiISOBJT/d3BM2iBEtERERERALPv/7l7wiaRQmWiA/FXD6EhN+eA8C+\n85+hNreQyLE9iLtlNKFdk6CqhoqZmzhw/wyorPFztOJrbcb9D2lXPQFAzl19qd69HguPotMd7xLV\nfSQhUXHse/VOCqf/xc+RnpwiIkI57/xMBgzqQGxsBEWF5cyZtZnCgnLOn9SXtPbxhIQY9/7mI8pK\nq/0dbsCKDIvhooE/Z2jn84mLTKKgdCcz1j1DxzaZDOh4Nm2i21JQupP3Vj3Ggi1v+ztcEZETrkXO\nwTKzWjNbZmarzGyamSX6ePtZZna6L7cp4gtREzNxtXWe+xP6ABCW2Y6aTfkU/2Em1av3EHPxAGKv\nH+HPMKWFxI+4DFdX670/xTMzJJTa0kJKV37kx8gE4Ac3jODMs7qzd08J77y5mhXLd5HeOZHwiFBy\nNhdQkF/m7xCDwi1jnmVc5vXs2r+BVxffw+JtH9A1eRAZyQP5Mue/vL7kAaIjErj2tIdJje3s73BF\nJJjdfrtnCjIt1YJV7pwbDGBmLwC3AA/6cPtZQAnQ6KvUmlmYc05NBtJiQtrGEj6kExXT1xExLJ2o\niZmU/m0epf+cD9WepKt6+U4iz+hGWM8UP0crvhaa2IHoXqMpXvA6MZlnEj/iMgrefRBXWcquJ79H\nwhnXED/8En+HedLq2SuFHj1T2L27mH/+fT7OeeabgXOwasVubrxlFKltY/0baIDrkzaazLRR7Ny/\nnsezr8bheSENIyQkjNo6T8tf2/iujO9zA+0TepJXus2fIYtIMFu2zN8RNMuJGEVwHtDp4AMzu9PM\nFprZCjO7r8H8t81ssZmtNrMfNZg/wcyWmNlyM/vUzDKAm4A7vK1kZ5pZhpl95t3mp2bWxbvu82b2\nNzObD/zxBDxXOYlFnZeJhYZQ8dE6KmZsILxXW0J7pNQnVwARZ3QDoHrRdn+FKS0kfvilWEgoJQvf\noHjxW0Sm9yeiY19/hyVenTp7OlJsWLevPrkCDrsv36xLcn8A1uyeU59cAThcfXIVYmFkthtFZU0Z\nWwpX+iVOERF/atEEy8xCgXHAu97H5wK9gBHAYOBUMxvjLX6dc+5UYBhwm5mlmFlb4B/AJc65QcAU\n51wu8DfgEefcYOfcHOCvwAvOuYHAy8DjDcJIB053zv20JZ+rSNSEPriqGmpyCqhesQuA6Il96pdH\nju9N/O1nUjFrE2WvBuc/MnJs8SOmUFddSdWutVRsWuCdd5mfo5J6yqR84xtexhAL5fpRj5Ke1I+X\nFtxFcUXeiYlLRCSAtFQXwWgzW4an5WoN8Il3/rneaan3cRyehGs2nqRqsnd+Z+/8tsBs51wOgHOu\n4Bj7GwVc7L3/Eoe3Vr3unKs92krelrIfAaSlpZGdnd2Ep9hySkpKAiaWlpSau4NUfwfhIyHt4wkf\n3BELMdpOu65+ftR5mZQ88QVREzJp84cLqJq/laKfvAN1rfPH3pbcXPKyGzc4QHxuLvEtHM+JEpac\nTlSPUVhICBm/X1U/P27EFPLfvu84a7YuW3JzWdXIz67c3MqWDeYI27ftB6BX79T6boHAYfcDQW5u\nLtnZuxpfvji35YI5ioMtUn3SzsCww7oImoVyw+gnGJx+Hv9a8CsWbnnnhMZ2UFVV1UnxHXoyOVl+\nF50smlKfg4uKAFgWZPXfoudgmVkM8BGec7AeBwx4yDn394aFzSwLOAcY5ZwrM7NsIMpHsZQea4Fz\n7mngaYBhw4a5rKwsH+3y28nOziZQYmlJxau+oJSd/g7DJ6LOy8RCjJKnv6R6pbf16uIBRI3tScyV\nQ4n/xVjcgQoqPlhD1Lhe1BWUUTV/q5+j9r2uGRn0zxrdqLJ5hbMoWN7CAZ0gccMvxUJCyJ/2EBU5\nCwFoM+Y64gZfSET6AKK6jyC65ygAorqPIGHM9RTPfxVXecyPp6DUNSOD1EZ+dlVVrGPjug0tG1AD\nmzbms2lDHj16pXLdDSNYuXwXiUnRJLSJIvvTTXTvkUxCQiQAQ09NJy+vlLVf7T1h8R2UkZFBVlZm\no8sXr1zKqlXfXM5X1u2Zy7o988hMG8WPs55n8dYPSY7tSGJ0GhFh0QztPJEVOz6lsqaUYV0mkZO/\njPwTfA5WRETESfEdejI5WX4XnSyaVJ8jPIOCBVv9t+gw7d5k6TbgbTN7Ck+ydb+ZveycKzGzTkA1\n0AYo9JbvA5zm3cSXwFNm1s05l2Nmyd5WrGIgocGu5gJT8bRefR+Y05LPS+RIURMzcXWO0hcW4QrL\nAbDwUKLG9iQkOQYLC8GSY2jz+/MBqFqwlYJWmGCdrDyjB9ZR9PGj1BZ7ukRZaARxgy8kfsQUUr7z\nvw3KTiF+xBTKvppBTStLsALdc88sZMIFfRgwsAM9eqWyv6icWTM307VbEpdOHVRf7juTT2HTxny/\nJFjB4MnZ13HRwDsZ2vl8MoedTmHZLj5e+zTn9b0JgIGdxjGw0zgAnv/yZ8zL0SAXItJMTz/t7wia\npcWvg+WcW2pmK4DLnXMvmVlfYJ6ZgWckwCuB6cBNZrYGWIcnscI5t8/bje9NMwsB9gLjgWnAG2Z2\nEfBj7/Scmd0J7AN+0NLPS6Shgqkvf21exfR17J7+JwBKHv/8RIckJ9C2+79+1YiSha+z/trXAch/\n8+4THZIcRVVVLe++tZp331r9tWWLF2rgmcaqrCnjtSX38dqSw7u/zt4YnBcEFRHxtRZJsJxzcUc8\nntTg/mPAY0dZbeIxtvUh8OER89YDA48oevZR1r22cRGLiIiIiEhA+ZF3YPEga8lq8RYsERERERGR\nJlu/3t8RNMuJuA6WiIiIiIjISUEJloiIiIiIiI8owRIREREREfERnYMlIiIiIiKBZ/Bgf0fQLEqw\nREREREQk8Dz6qL8jaBZ1ERQREREREfERJVgiIiIiIhJ4rrzSMwUZdREUv4m/dTTxt472dxgtLjs7\nm6ysLH+HEXBSJ99D6uR7/B1Gs6hOv71zJ2Ry7oRMf4cBBHd9ThpwB5MG3OHvMAJKdna2v0MQEV/Z\nvt3fETSLWrBERERERER8RAmWiIiIiIiIjyjBEhERERER8RGdgyUiIiIiIoFn1Ch/R9AsSrBERERE\nRCTwPPSQvyNoFnURFBERERER8RElWCIiIiIiEnguucQzBRl1ERQRERERkcCTn+/vCJpFLVgiIiIi\nIiI+ogRLRERERETER5RgiYiIiIiI+IjOwRIRERERkcAzbpy/I2gWJVgiIiIiIhJ4fvtbf0fQLOoi\nKCIiIiIi4iNKsEREREREJPBMnOiZgoy6CIqIiIiISOApL/d3BM2iFiwREREREREf+f/t3Xt8VdWd\n9/HPLyEhXAJyE+VSqIDBCooOpirWxqoVrNpqpZen09bRp60zter0PtOOl9ba+4zt2HbGthafaauj\nVqtOLVp8jFWrQLEqiEVU4gURhQAmQQgka/44B0QBzYkH9jnh8369zuvss/c6O9+TxQ75Za+1twWW\nJEmSJBWJBZYkSZIkFYlzsCRJkiSVnpNOyjpBt1hgSZIkSSo9n/981gm6xSGCkiRJklQkFliSJEmS\nSk9DQ+5RZiywJEmSJKlILLAkSZIkqUi8yIUkSQVoeeRiWh/92i7Zd/8DLqD2wAt3yb73FAtbbuTq\nqz+edQwATpp0PidP/sesY3TL7bOXMOe2pVnHAGB8XVWXR4mtuvFimm/aNcdnoQa/9wKGntr147nl\n8ntp+/GfdmGiruv3D0dSe860LrVd+Id/ZdGcywra/9W/71q7dz35Av0GjaJ/QXvPnmewJEmSJKlI\nLLAkSZIklZynJ/Zh3dEHZx2jYBZYkiRJkkrO44fU0nxK14YqlhILLEmSJEklp3JTJ7GhPesYBbPA\nkiRJklRy3nn9KsZ+9WdZxyiYBZYkSZIkFYkFliRJkiQViffBkiTpTarsO4a9T3wSgJQ66WxfTfvK\nOaxb8Cn6TTiPPmM+RmXfUXRufJG2pT+gbWlh94zRrtO7V1/ee9DnOXT0ifTvPYjmtueYs+RnjBhY\nx+QR72Jgn2E0tz3H/yz6AfOe+m3WcUtWdXUlJ5xYx+SD96Vfv2rWrnmZu+96kjXNL3PiyQcwfJ9a\nKiqCi756G+vbNmUdd6uBx/49wz96OQDLvnwAm55/jKiqYeQ/3kzNfm+noqY/L17zBdbM/teMk26v\n74cPYcC/HAfAiyf+jI6mNfQ+Zhz9Pz2NyjGDoH0zG+58gpe+Pgc2bt7t+foNGsUpX87d1yt1drJx\n/RqeX3o382/4MrXDxnHYad9k0L5vo6KyF7f98CSalz+82zPuKm94BisiOiLiwYhYFBHXRUTfQr9I\nRFwUEZ/vXsRX7WdERFz/ZvcjSdKusGnNA6yd91E2rbqHPm/5MH3HnU3V4Ho2PHcT6x48n9TZzoCD\nv0/10KOzjqq8Tx99JcfWncWKdUu5ZsGFLHjmVsYMPpixgw/i/mW/4boHLqFP9QDOOPz7DO03Ouu4\nJevvPlHPO965Hy+sbOWmGx7h4YdWMGr0XlRVV7LsyWaaV6/POuIO1dZ/gNTZkV+emVtZUUlH2xra\nFt6WYbI3VjOjjtTRmVuePhGAXnV7s/mJ1bR8+042PbKSvqdNpt9Z9VnGpHn5Qu675lxebJrH2EPe\nx/jDP0plVQ1rn3uENc89kmm2XaUrZ7BeTilNAYiIXwFnA5mU8Sml54DTs/jakiS9kc6Nq2hfOYfK\nvmOoGXkqUTWANffNhJT7i31U9GbgIT+k14C30b7qjxmn1cTh06gbfgTPrXuMHzZ+jEQCIAgqKnrR\n0Znrt2G1Yzh+4ifYZ8B4VrU9k2XkkjR+whDGjR/C88+38PP/nEvKfRuJgJRg0cPP86lPH8HQYf2y\nDfoalXvtS58J02iZdx19695Bbf0HaL75G6SNbaz40QcZcNTHqT3s/VnH3KGKYf2oOmQkG2YvoXrq\nKGpm1NH2H/fR9vO5sClXdG166Dl6H/VWeo0fkmnWjW3NPP/4PfQbNJrRk2ZQVdOfVU3zWdU0n7fP\n/D5DRu/8PlfLJvVj5IFT6b8b8xZDoXOw7gbGA0TEbyNiQUQ8EhGf3NIgIqZHxAMR8VBE3PHaHUTE\nJyLi9xHRJ788P9/2N1vOjkXEuIi4PyIWRsQlEdGaXz82Ihbll8+IiBsiYnZELI2I72zzNc6KiMci\nYl5E/DQiLi/8WyNJUmF67/Nuhp+ykgGTL6Xj5eWsf/xHW4srgN7D301KHbSv/lOGKbXFWwZPAuDR\n5+/eWlwBJNLW4qoielG39xFs3Lyep9YszCRnqRs5ei8Ali55cWtxBbxquRTVHnY6UVFJ6/zraVlw\nI71HTaJ6xAFZx+qSmhPqiMoKNty2hA1zllI1YRiV44ZsLa4Aqo96KwCb/vxsVjEB2Hf/d3LaBQ9y\n8IwvsX7d8yz901Vdfu+yyf1Y++5sz8B1R5fnYEVEL2AGMDu/6syUUnNE9AHmR8RvyBVsPwWOTikt\ni4jBr9nHOcDxwPtSShsj4oaU0k/z2y4BzgL+HfgB8IOU0tURcfbrxJoCHAJsBJZExL8DHcC/AIcC\nLcD/Bx7ayWf6JPBJgOHDh9PY2NjVb8cu1draWjJZ9ObZnz2PfdqzFNqfQ9qaGLqTbe2r76flkQuo\nHvZOag/4Cn3HnU3r4q8BUHvQd6kZcRIvLfwnNq/b8VyDpqYmVr/Y9SzaXnt7AffMeYMCoCIqOeuI\nyxg16G1ced/5tGxYVVCWpqYmGlc3FvSeUtHUtLHrjXdxJdXevqnLx2htUxO1Xdxvbf16+3TMAAAU\nTUlEQVRMOjdtpH3FX4nqvnBcbsjg6t9e3O2s23qqqYlFBfxsGdq0fKc/W16rZvpEUvtmNi9rJvpU\nwUegz4yJtF5+LwC9j9+f2vPfwYa7nmD9NQ92K/uqxq7NlWtpanrd7auefoCHb/see+93OJOOPZfx\nh3+URXP+rUv7rl7fwXMLH2V1VWOX2peKrhRYfSJiS8/cDfw8v3xuRJyaXx4NTACGAX9MKS0DSCk1\nb7OfjwHPkCuutvTYpHxhtRfQH9gy2PUI4H355V8D39tJtjtSSusAImIxMAYYCty15WtHxHXA/jt6\nc0rpCuAKgKlTp6aGhobX+TbsPo2NjZRKFr159mfPY5/2LIX2Z8sjd9H66I63dbavpv2FO2hfdS+1\nB3yF3vvMoHXx1xhw8L/Rb8K5tCz+Om1LvrPjNwNjx45l8oFdz6LtLbzlRuhijbXljNTE4UcRxKuG\nCEZU8olplzNl1An8ct4/Mf+pmwrOMnbsWBomNxT8vlLQvmEJjy9Z2qW2zz6zDoAJ+w/dOiwQeNXy\nm1FdXdXlY3TVmrto3uGf1V+t1+BR1Iw7gqioYOyli7au718/s2gF1pixYxlayM+WRffSxnNv2K5i\nn1qqpowgKoJht5y5dX3NCXW0Xn4vNdPrGPjt99A+92nWnncTdBbeCWPGjmVSw7QutV246QEWPb7z\n7Rvb1rDy8XtY1TSfSceey4iJx3S5wDrqptX0G3Qn/T/70y61LxUFzcHaIiIagOOAI1JK6yOiEah5\ng/0sJHfGaRSwLL9uFrmC66GIOANo6GrwvG3/vNKBV0WUJGWosmZfakZ9kOqhRwHQ0fYUtZO+Qb8J\n59LePJfNLz1KzagPsvmlRWx+qWdO7i4nS1b+iSUr76Nu+BF8pmEWC57+PYP7jWCvPsOp7tWHQ0fP\n4OHld7BxcxtT33Iyy1Y/yGrnYG3nicdX88TSVYybMJQzP1HPwodWsNegPgwYWEPjHU+w37jBDBjQ\nG4BD/2YUq1a18dfFL2Sauf9hpxMVFay+5ZtsWDYfgIFHn0n/KSdRPWoyNfvV02f8EQDU7FfPgKPP\nomXuNaSNbVnGzuU5oY6oCFqvuJ9NC1cA0Oe0ydQcM56+f3sotV88hvTSBjbc+ig1x06gs3k97XOf\nzixvnwF785aDT2bY2NxQv7Y1z1JTuzcjJr6L2qG5YYwjDzye/kPG8PTDt2SWs5i6W5AMBNbki6uJ\nwOH59fcDP46It24ZIrjNWay/AD8Bbo6IE/IXrKgFVkREFfARYPk2+3k/8N/AhwrMNh+4LCIGkRsi\n+H5yxZ0kSbtU1aBDGXT4r+nctI4Nz99Gy8IvMvCwXwBQPfjtVB/+awBaFl9M62ILrFLwoz+eyXsP\n+gKHjj6RuqlHsmb9Cm7/6xWccEBuhsJBI4/loJHHAjDr/s9x3zILrB35xc/mM/09E5l80L6MmzCU\ndWtf5q47n2TMWwdx+odeuYjBKaceyBOPr868wMpdPbCTtbdfRkdLbuhnVFbTf8pJ1NbPZMgpX9mm\n7Uxq62eyfvEcNpdCgTWjjtSZaLvqz6Q1LwMQVZXUHDOeisF9iV4VxOC+DLz0RADa5z1Nc4YF1uCR\nk5n2f35E+4aXWLGkkb/87hsMGLYfbz/9lbP5k449j9bmZ/b4Ams2cHZEPAosIVcQkVJ6MT+v6YaI\nqABeIDfnivz2e/KXa/9dRBxPbq7UXODF/POWYbPnA7+MiK/kv9a6rgZLKS2PiEuBeUAz8NdC3i9J\nUqE61j/Fiusrd7it+a5jd3MaFWLj5vVc+8DFXPvAq4eF/fHxX2aUqDy1t3dw842PcPON2//hYMH8\nbC+ysCPPfP3I7da1zr+Ox864DoDVN1ywuyN1WfOHfrXdug2zl/D87O8C0PrDe3Z3pB1qW/MsV3/p\nLTvctn7t8p1u6wnesMBKKW13ZcSU0kZyF7zYUfvfA79/zbqLtlm+jVfmWv0k/3it5cDhKaUUER8C\n6vLvbQIm5ZdnkRtiuGW/J23z/l+nlK7IX5jjRsA7A0qSJEna5Up1ztLfAJdHRABrgTPfoP1rXRQR\nx5GbF3Y7FliSJElSWXl8Sn9GTz6i7O6DVZIFVkrpbmDndx174/d/vohxJEmSJO1mTx/QlwENh2Qd\no2CF3mhYkiRJkna5vi9tpuqFNVnHKJgFliRJkqSSc/jvmhn1nauzjlEwCyxJkiRJKhILLEmSJEkq\nEgssSZIkSSqSkryKoCRJpar2wAupPfDCrGNoJybXnspnTv5B1jHK3run1/Hu6XVZxwCgsbGxy22H\nnnohQ08tz+Oz9pxp1J4zLesYBZt8/GeZfPxnu9y+sbGRhoaGrjWe28V2JcYCS5IkSVLp+dznsk7Q\nLRZYkiRJkkrPySdnnaBbnIMlSZIkqfQsWZJ7lBnPYEmSJEkqPZ/6VO65gHl4pcAzWJIkSZJUJBZY\nkiRJklQkFliSJEmSVCQWWJIkSZJUJF7kQpIkSVLp+epXs07QLRZYkiRJkkrPccdlnaBbHCIoSZIk\nqfQ8+GDuUWY8gyVJkiSp9Jx/fu7Z+2BJkiRJ0p7JAkuSJEmSisQCS5IkSZKKxAJLkiRJkorEi1xI\nkiRJKj2XXpp1gm6xwJIkSZJUeo48MusE3eIQQUmSJEml509/yj3KjGewJEmSJJWef/7n3LP3wZIk\nSZKkPZMFliRJkiQViQWWJEmSJBWJBZYkSZIkFYkXuZAkSZJUei67LOsE3WKBJUmSJKn0TJmSdYJu\nscAqQbV/uYrHZh27S/Y9+L0XMPTUC7vcvuXye2n78a65/0C/fziS2nOm7ZJ9S5IkqczNmZN7Pu64\nbHMUyAJLkiRJUum55JLcc5kVWF7kQpIkSZKKxAJLkiRJkorEAkuSJEmSisQCS5IkSZKKxItcSJIk\nSSo9//mfWSfoFgssSZIkSaWnri7rBN3iEMEyMvDYv2f/WR3sP6uDqn32ByCqahj1xdsZ/x/r2H9W\nB4Omf3a3ZOn74UPYZ/EX2GfxF6gcOwiA3seMY8j1H2Pv+eex972fZsAl06G3NbwkSZK64ZZbco8y\nk3mBFREpIn65zeteEfFiRPxP/vUpEfHl7BKWjtr6D5A6O/LLM3MrKyrpaFtD28LbdmuWmhl1pI7O\n3PL0iQD0qtubzU+spuXbd7LpkZX0PW0y/c6q3625JEmS1EN8//u5R5nJvMAC2oBJEdEn//p4YPmW\njSmlm1NK33qzXyQiyvpUSuVe+9JnwjRa5l3H5jXLqa3/AABpYxsrfvRB2h763W7LUjGsH1WHjGTD\n7CV0rGyhZkbu9G3bz+ey7ku/4+XrH6blu40A9Bo/ZLflkiRJkrJWCgUWwK3Ae/LLHwau3rIhIs6I\niMvzyzdFxMfyy5+KiF/ll8dFxOyIWBARd0fExPz6WRHxHxExF/jO7vxAxVZ72OlERSWt86+nZcGN\n9B41ieoRB2SSpeaEOqKygg23LWHDnKVUTRhG5bghsKlza5vqo94KwKY/P5tJRkmSJCkLpXJW5xrg\ngvywwIOAK4F37KDdJ4F7I2IZ8Dng8Pz6K4CzU0pLI+LtwI+Bd+W3jQKOTCl1vHZnEfHJ/D4ZPnw4\njY2NxftEb0Lv9vbt1tXWz6Rz00baV/yVqO4Lx+WGDK7+7cUF7fuppiYWFfA5hzYtZ+hr1tVMn0hq\n38zmZc1Enyr4CPSZMZHWy+/N5T9+f2rPfwcb7nqC9dc8+LpZVjVuKih/OWptbS2Zf1sqDvu0Z7E/\nexb7s+exT3uWQvpzytq1ADxYZv1fEgVWSunhiBhL7uzVra/TbmVEXADcCZyaUmqOiP7AkcB1EbGl\nae9t3nbdjoqr/P6uIFecMXXq1NTQ0PAmP0lxLPjLVa963WvwKGrGHUFUVDD20kVb1/evn1lwgTVm\n7FiGFvA5WxbdSxvPbX1dsU8tVVNGEBXBsFvO3Lq+5oQ6Wi+/l5rpdQz89nton/s0a8+7CTrT62aZ\n1DCtoPzlqLGxkVL5t6XisE97FvuzZ7E/ex77tGcpqD/32gug7Pq/JAqsvJuB7wENwOtN3JkMrAZG\n5F9XAGtTSlN20r6tWAGz0v+w04mKClbf8k02LJsPwMCjz6T/lJOoHjWZmv3q6TP+CABq9qtnwNFn\n0TL3GtLG4n/0mhPqiIqg9Yr72bRwBQB9TptMzTHj6fu3h1L7xWNIL21gw62PUnPsBDqb19M+9+mi\n55AkSVIP91//lXWCbimlAutKcoXSwoho2FGDiKgHZgCHAHdFxO0ppWURsSwiZqaUrovcaayDUkoP\n7b7ou1bu6oGdrL39MjpaVgEQldX0n3IStfUzGXLKV7ZpO5Pa+pmsXzyHzbuiwJpRR+pMtF31Z9Ka\nl3NZqiqpOWY8FYP7Er0qiMF9GXjpiQC0z3uaZgssSZIkFWr06KwTdEvJFFgppWeBH+5se0T0Bn4K\n/F1K6bmI+BxwZUS8C/gI8JOI+CpQRW5OV48psJ75+pHbrWudfx2PnXEdAKtvuGC3ZWn+0K+2W7dh\n9hKen/3dXK4f3rPbskiSJKkH++//zj1/8IPZ5ihQ5gVWSqn/DtY1Ao355VnArPymg7dpczO5YYUA\ny4DpO9jPGUWMKkmSJGl3+clPcs9lVmCVymXaJUmSJKnsWWBJkiRJUpFYYEmSJElSkVhgSZIkSVKR\nZH6RC0mSJEnazvXXZ52gWyywJEmSJJWeoUOzTtAtDhGUJEmSVHpmzco9yoxnsEpQyyEf52/+8RdZ\nxwCg9pxp1J4zLesYkiRJ2tNsKa7OOCPLFAXzDJYkSZIkFYkFliRJkiQViQWWJEmSJBWJBZYkSZIk\nFYkXuZAkSZJUem69NesE3WKBJUmSJKn09O2bdYJucYigJEmSpNLz4x/nHmXGAkuSJElS6bn22tyj\nzFhgSZIkSVKRWGBJkiRJUpFYYEmSJElSkVhgSZIkSVKRREop6wwlISJeBJ7KOkfeUGBV1iFUNPZn\nz2Of9iz2Z89if/Y89mnPUs79OSalNOyNGllglaCI+HNKaWrWOVQc9mfPY5/2LPZnz2J/9jz2ac+y\nJ/SnQwQlSZIkqUgssCRJkiSpSCywStMVWQdQUdmfPY992rPYnz2L/dnz2Kc9S4/vT+dgSZIkSVKR\neAZLkiRJkorEAkuSJEmSisQCq8RExPSIWBIRj0fEl7POozcnIpoiYmFEPBgRf846jwoXEVdGxAsR\nsWibdYMj4g8RsTT/PCjLjOq6nfTnRRGxPH+cPhgRJ2aZUV0XEaMj4s6IWBwRj0TEefn1HqNl6HX6\n02O0DEVETUTMi4iH8v15cX59jz8+nYNVQiKiEngMOB54FpgPfDiltDjTYOq2iGgCpqaUyvWGenu8\niDgaaAX+X0ppUn7dd4DmlNK38n8IGZRS+lKWOdU1O+nPi4DWlNL3ssymwkXEvsC+KaUHIqIWWAC8\nDzgDj9Gy8zr9+QE8RstORATQL6XUGhFVwD3AecBp9PDj0zNYpaUeeDyl9GRKqR24BnhvxpmkPVpK\n6Y9A82tWvxe4Kr98FblfAFQGdtKfKlMppRUppQfyyy3Ao8BIPEbL0uv0p8pQymnNv6zKPxJ7wPFp\ngVVaRgLPbPP6WfzBUu4SMCciFkTEJ7MOo6IZnlJakV9+HhieZRgVxWci4uH8EMIeN1xlTxARY4FD\ngLl4jJa91/QneIyWpYiojIgHgReAP6SU5pI7HtdExDxgNjC+0OGDpT4FwwJL2rWOSilNAWYAn84P\nT1IPknLjrB1rXd5+AuwHTAFWAN/PNo4KFRH9gd8A56eUXtp2m8do+dlBf3qMlqmUUkf+96BRQH1E\nTMpv2gi8K6V0MPASMD0iDge+DNyRUpoA3JF/vTPHpJSmpJSm7sKP0C0WWKVlOTB6m9ej8utUplJK\ny/PPLwA3khsGqvK3Mj9XYMucgRcyzqM3IaW0Mv9LQCfwUzxOy0p+bsdvgF+llG7Ir/YYLVM76k+P\n0fKXUloL3AlMB1YC++TnZu0LvEgPGz5ogVVa5gMTIuKtEVENfAi4OeNM6qaI6JefpEtE9APeDSx6\n/XepTNwMfDy//HHgpgyz6E3a8ot43ql4nJaN/CT6nwOPppT+dZtNHqNlaGf96TFaniJiWETslV/u\nQ+4ibn8lf3zmL+62ABjLNsMHuzi8t6SnYHgVwRKTv/ToZUAlcGVK6RsZR1I3RcR+5M5aAfQCfm1/\nlp+IuBpoAIaS+6vbhcBvgWuBtwBPAR9IKXnhhDKwk/5sIDf0KAFNwKe2+Q9eJSwijgLuBhYCnfnV\n/0xu3o7HaJl5nf78MB6jZSciDiJ3FqqS3Emda1NKX4uIIbz6+Py/wC+AzwD3pJT22mYfa1JK283D\nioiRKaXlEbE38AfgM/mLGJUECyxJkiRJmYmIC4D1wCeAhpTSivyZy8aUUt0bvPciSuwy/g4RlCRJ\nkrTbvNHwwXyzHQ7vLYcpGL2yDiBJkiRpj7IvcFV+HtaW4YP/ExH3AddGxFnkh/cCRMQI4GcppRPJ\nzcu6MTdlb+sUjNlZfIidcYigJEmSJBWJQwQlSZIkqUgssCRJkiSpSJyDJUnq8fKXBb4j/3IfoIPc\nzS0B1qeUjswkmCSpx3EOliRpj1KKl/SVJPUcDhGUJO3RIqI1/9wQEXdFxE0R8WREfCsiPhIR8yJi\nYUSMy7cbFhG/iYj5+ce0bD+BJKmUWGBJkvSKg4GzgQOAjwL7p5TqgZ8Bn8m3+QHwbymlw4D357dJ\nkgQ4B0uSpG3NTymtAIiIJ4Db8+sXAsfkl48D3pa/BwvAgIjon1Jq3a1JJUklyQJLkqRXbNxmuXOb\n15288n9mBXB4SmnD7gwmSSoPDhGUJKkwt/PKcEEiYkqGWSRJJcYCS5KkwpwLTI2IhyNiMbk5W5Ik\nAV6mXZIkSZKKxjNYkiRJklQkFliSJEmSVCQWWJIkSZJUJBZYkiRJklQkFliSJEmSVCQWWJIkSZJU\nJBZYkiRJklQk/wsyxfRxBnZQEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x123151e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyomo.environ import *\n",
    "import pandas as pd\n",
    "\n",
    "def JobShop(TASKS, solver='glpk', tclean = 0):\n",
    "\n",
    "    model = ConcreteModel()\n",
    "\n",
    "    JOBS = set()\n",
    "    MACHINES = set()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        JOBS.add(j)\n",
    "        MACHINES.add(m)\n",
    "        \n",
    "    BigM = 1 + sum([TASKS[(j,m)]['dur'] for (j,m) in TASKS.keys()])\n",
    "    \n",
    "    model.start = Var(JOBS, MACHINES, domain = NonNegativeReals)\n",
    "    model.makespan = Var(domain=NonNegativeReals)\n",
    "    model.y = Var(JOBS,JOBS,MACHINES, domain = Boolean)\n",
    "\n",
    "    model.Obj = Objective(expr = model.makespan, sense = minimize)\n",
    "\n",
    "    model.cons = ConstraintList()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] + tclean <= model.makespan)\n",
    "        if 'prec' in TASKS[(j,m)]:\n",
    "            (k,n) = TASKS[(j,m)]['prec']\n",
    "            model.cons.add(model.start[j,m] >= model.start[k,n] + TASKS[(k,n)]['dur'])\n",
    "        \n",
    "    for m in MACHINES:\n",
    "        for j in JOBS:\n",
    "            for k in JOBS:\n",
    "                if (j < k) and (j,m) in TASKS.keys() and (k,m) in TASKS.keys():\n",
    "                    model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] + tclean\n",
    "                                   <= model.start[k,m] + BigM*(1-model.y[j,k,m]))\n",
    "                    model.cons.add(model.start[k,m] + TASKS[(k,m)]['dur']  + tclean\n",
    "                                   <= model.start[j,m] + BigM*(model.y[j,k,m]))\n",
    "\n",
    "    # solve with indicated solver\n",
    "    SolverFactory(solver).solve(model)\n",
    "    \n",
    "    # create pandas dataframe with the optimal schedule\n",
    "    results = [[j,m,model.start[j,m](),TASKS[(j,m)]['dur'], model.start[j,m]() + TASKS[(j,m)]['dur']] \n",
    "             for (j,m) in TASKS]\n",
    "    schedule = pd.DataFrame(results,columns=['Job','Machine','Start','Duration','Finish'])\n",
    "    schedule = schedule.sort_values(by='Start')\n",
    "    schedule.set_index(['Job',\"Machine\"], inplace=True)\n",
    "    \n",
    "    return schedule\n",
    "\n",
    "\n",
    "TASKS = Recipe(['A1','A2'],['Mixer','Reactor','Separator','Packaging'],[1,5,4,1.5])\n",
    "TASKS.update(Recipe(['B1','B2'],['Separator','Packaging'],[4.5,1]))\n",
    "TASKS.update(Recipe(['C1','C2'],['Separator','Reactor','Packaging'],[5,3,1.5]))\n",
    "\n",
    "schedule = JobShop(TASKS, solver='gurobi', tclean=0.5)\n",
    "Visualize(schedule)\n",
    "print(\"Makespan = \", schedule['Finish'].max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Zero Wait Policy\n",
    "\n",
    "One of the issues in the use of job shop scheduling for batch processing are situations where there it isn't possible to store intermediate materials. If there is no way to store intermediates, either in the processing equipment or in external vessels, then a **zero-wait** policy may be appropriate. \n",
    "\n",
    "A zero-wait policy requires subsequent processing machines to be available immediately upon completion of any task. To implement this policy, the usual precident sequencing constraint of a job shop scheduling problem, i.e.,\n",
    "\n",
    "\\begin{align*}\n",
    "\\text{start}_{k,n}+\\text{Dur}_{k,n} \\leq \\text{start}_{j,m}\\ \\ \\ \\ \\text{for } (k,n) =\\text{Prec}_{j,m}\n",
    "\\end{align*}\n",
    "\n",
    "is changed to \n",
    "\n",
    "\\begin{align*}\n",
    "\\text{start}_{k,n}+\\text{Dur}_{k,n} = \\text{start}_{j,m}\\ \\ \\ \\ \\text{for } (k,n) =\\text{Prec}_{j,m}\\text{ and ZW is True}\n",
    "\\end{align*}\n",
    "\n",
    "if the zero-wait policy is in effect. \n",
    "\n",
    "While this could be implemented on an equipment or product specific basis, here we add an optional ZW flag to the JobShop function that, by default, is set to False."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Makespan =  32.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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z4/nnx4E6HUFR4/GyZXMBDQ0+Zv77UC69rC87thUxdHgX0gckU3C4ik6dY7Es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S/brjzZbuXLtts7I1JKB77XThZYJSgifp9Sqs86hwpn25Uv26582Xbly7YrT7Zb+bLtuoZDBCVJ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\nSZKkIrHAkiRJkqQi+f/lQ4Ft+uqelwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1201b08d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyomo.environ import *\n",
    "import pandas as pd\n",
    "\n",
    "def JobShop(TASKS, solver='glpk', tclean = 0, ZW = False):\n",
    "\n",
    "    model = ConcreteModel()\n",
    "\n",
    "    JOBS = set()\n",
    "    MACHINES = set()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        JOBS.add(j)\n",
    "        MACHINES.add(m)\n",
    "        \n",
    "    BigM = 1 + sum([TASKS[(j,m)]['dur'] for (j,m) in TASKS.keys()])\n",
    "    \n",
    "    model.start = Var(JOBS, MACHINES, domain = NonNegativeReals)\n",
    "    model.makespan = Var(domain=NonNegativeReals)\n",
    "    model.y = Var(JOBS,JOBS,MACHINES, domain = Boolean)\n",
    "\n",
    "    model.Obj = Objective(expr = model.makespan, sense = minimize)\n",
    "\n",
    "    model.cons = ConstraintList()\n",
    "    for (j,m) in TASKS.keys():\n",
    "        model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] + tclean <= model.makespan)\n",
    "        if 'prec' in TASKS[(j,m)]:\n",
    "            (k,n) = TASKS[(j,m)]['prec']\n",
    "            if ZW:\n",
    "                model.cons.add(model.start[j,m] == model.start[k,n] + TASKS[(k,n)]['dur'])\n",
    "            else:\n",
    "                model.cons.add(model.start[j,m] >= model.start[k,n] + TASKS[(k,n)]['dur'])\n",
    "        \n",
    "    for m in MACHINES:\n",
    "        for j in JOBS:\n",
    "            for k in JOBS:\n",
    "                if (j < k) and (j,m) in TASKS.keys() and (k,m) in TASKS.keys():\n",
    "                    model.cons.add(model.start[j,m] + TASKS[(j,m)]['dur'] + tclean\n",
    "                                   <= model.start[k,m] + BigM*(1-model.y[j,k,m]))\n",
    "                    model.cons.add(model.start[k,m] + TASKS[(k,m)]['dur']  + tclean\n",
    "                                   <= model.start[j,m] + BigM*(model.y[j,k,m]))\n",
    "\n",
    "    # solve with indicated solver\n",
    "    SolverFactory(solver).solve(model)\n",
    "    \n",
    "    # create pandas dataframe with the optimal schedule\n",
    "    results = [[j,m,model.start[j,m](),TASKS[(j,m)]['dur'], model.start[j,m]() + TASKS[(j,m)]['dur']] \n",
    "             for (j,m) in TASKS]\n",
    "    schedule = pd.DataFrame(results,columns=['Job','Machine','Start','Duration','Finish'])\n",
    "    schedule = schedule.sort_values(by='Start')\n",
    "    schedule.set_index(['Job',\"Machine\"], inplace=True)\n",
    "    \n",
    "    return schedule\n",
    "\n",
    "\n",
    "TASKS = Recipe(['A1','A2'],['Mixer','Reactor','Separator','Packaging'],[1,5,4,1.5])\n",
    "TASKS.update(Recipe(['B1','B2'],['Separator','Packaging'],[4.5,1]))\n",
    "TASKS.update(Recipe(['C1','C2'],['Separator','Reactor','Packaging'],[5,3,1.5]))\n",
    "\n",
    "schedule = JobShop(TASKS, solver='gurobi', tclean=0.5, ZW=True)\n",
    "Visualize(schedule)\n",
    "print(\"Makespan = \", schedule['Finish'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Machine Bottleneck](http://nbviewer.jupyter.org/github/jckantor/CBE40455/blob/master/notebooks/04.02-Machine-Bottleneck.ipynb) | [Contents](toc.ipynb) | [Jesuit Volunteer Corps](http://nbviewer.jupyter.org/github/jckantor/CBE40455/blob/master/notebooks/04.04-Jesuit-Volunteer-Corps.ipynb) ><p><a href=\"https://colab.research.google.com/github/jckantor/CBE40455/blob/master/notebooks/04.03-Job-Shop-Scheduling.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a><p><a href=\"https://raw.githubusercontent.com/jckantor/CBE40455/master/notebooks/04.03-Job-Shop-Scheduling.ipynb\"><img align=\"left\" src=\"https://img.shields.io/badge/Github-Download-blue.svg\" alt=\"Download\" title=\"Download Notebook\"></a>"
   ]
  }
 ],
 "metadata": {
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   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
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