{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b1b21dfb",
   "metadata": {},
   "source": [
    "# Unit Commitment\n",
    "\n",
    "TODO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5c0dec00",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m environment at `~/Packages/MIPLearn/dev/docs/benchmarks/Project.toml`\n"
     ]
    }
   ],
   "source": [
    "using Distributed\n",
    "# addprocs(17 - nprocs())\n",
    "@everywhere using Pkg\n",
    "@everywhere Pkg.activate(\".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5da58a62",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Precompiling MIPLearn [2b1277c3-b477-4c49-a15e-7ba350325c68]\n",
      "└ @ Base loading.jl:1317\n"
     ]
    }
   ],
   "source": [
    "@everywhere using MIPLearn\n",
    "@everywhere using MIPLearn.BB\n",
    "@everywhere using UnitCommitment\n",
    "@everywhere using Gurobi\n",
    "@everywhere using Random\n",
    "@everywhere using JuMP\n",
    "@everywhere using Logging\n",
    "@everywhere import UnitCommitment: XavQiuAhm2021\n",
    "@everywhere Logging.disable_logging(Logging.Warn);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "444dbbb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "0.0%┣                                               ┫ 0/45 [00:00<00:-2, -0s/it]\n",
      "2.2%┣█                                          ┫ 1/45 [00:42<Inf:Inf, InfGs/it]\n",
      "WARNING: Force throwing a SIGINT\n"
     ]
    }
   ],
   "source": [
    "@everywhere Base.@kwdef struct UnitCommitmentData\n",
    "    case::String\n",
    "    hours::Int\n",
    "    seed::Int\n",
    "end\n",
    "\n",
    "@everywhere function build_uc_model(data::UnitCommitmentData)\n",
    "    instance = UnitCommitment.slice(\n",
    "        UnitCommitment.read_benchmark(\"matpower/$(data.case)/2017-02-01\"),\n",
    "        1:data.hours,\n",
    "    )\n",
    "    Random.seed!(data.seed)\n",
    "    UnitCommitment.randomize!(\n",
    "        instance,\n",
    "        XavQiuAhm2021.Randomization(),\n",
    "    )\n",
    "    model = UnitCommitment.build_model(\n",
    "        instance = instance,\n",
    "        variable_names = true,\n",
    "    )\n",
    "    @lazycb(\n",
    "        model,\n",
    "        UnitCommitment.find_lazy,\n",
    "        UnitCommitment.enforce_lazy,\n",
    "    )\n",
    "    return model\n",
    "end\n",
    "\n",
    "instances = MIPLearn.save(\n",
    "    [\n",
    "        UnitCommitmentData(\n",
    "            case = \"case1888rte\",\n",
    "            hours = 4,\n",
    "            seed = i,\n",
    "        )\n",
    "        for i in 1:50\n",
    "    ],\n",
    "    \"uc\",\n",
    ")\n",
    "\n",
    "MIPLearn.run_benchmarks(\n",
    "    optimizer = Gurobi.Optimizer,\n",
    "    train_instances = instances[1:45],\n",
    "    test_instances = instances[46:50],\n",
    "    build_model = build_uc_model,\n",
    "    progress = true,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2caac26f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Julia 1.6.0",
   "language": "julia",
   "name": "julia-1.6"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}