Direct_MIP_Return.ipynb

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   "source": [
    "from gurobipy import *  #引用gurobi求解包\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "def Direct_MIP_Return_solver(s,timebound):\n",
    "    # Model\n",
    "    OP = Model(\"DMR\")  #定义模型\n",
    "    \n",
    "    I = len(s.Ki)\n",
    "    J = s.number_of_batch\n",
    "    numberperunit = int(s.number_of_order / s.number_of_batch)\n",
    "    K = len(s.Ik)\n",
    "    B = len(s.mb)\n",
    "\n",
    "    y = OP.addVars(I, J, vtype=GRB.BINARY, name=\"y\")  #定义决策变量\n",
    "    z = OP.addVars(J, K, vtype=GRB.BINARY, name=\"z\")\n",
    "\n",
    "    d = []\n",
    "    for j in range(J):\n",
    "        d.append([])\n",
    "        for b in range(B):\n",
    "            d[j].append(\n",
    "                OP.addVar(lb=0,\n",
    "                          ub=s.mb[b],\n",
    "                          vtype=GRB.CONTINUOUS,\n",
    "                          name=\"d[%d,%d]\" % (j, b)))\n",
    "\n",
    "    delta = OP.addVars(J, B, vtype=GRB.BINARY, name=\"delta\")\n",
    "\n",
    "# The objective is to minimize the costs\n",
    "\n",
    "    OP.setObjective(\n",
    "        s.alpha * quicksum(z[j, k] for j in range(J) for k in range(K)) +\n",
    "        (1 - s.alpha) * (2 * quicksum(d[j][b] for j in range(J) for b in range(B))+s.number_of_batch*len(s.mb)), GRB.MINIMIZE)\n",
    "    #OP.setObjective(quicksum(delta[j, b] for j in range(J) for b in range(B)), GRB.MINIMIZE) \n",
    "\n",
    "    OP.addConstrs(\n",
    "        sum(y[i, j] for i in range(I)) == numberperunit for j in range(J))\n",
    "    OP.addConstrs(sum(y[i, j] for j in range(J)) == 1 for i in range(I))\n",
    "    OP.addConstrs(\n",
    "        min(numberperunit, len(s.Ik[k])) * z[j, k] >= sum(y[i, j]\n",
    "                                                          for i in s.Ik[k])\n",
    "        for j in range(J) for k in range(K))\n",
    "    OP.addConstrs(\n",
    "        min(numberperunit, len(s.Ib[b])) * delta[j, b] >= sum(y[i, j]\n",
    "                                                              for i in s.Ib[b])\n",
    "        for j in range(J) for b in range(B))\n",
    "    OP.addConstrs(delta[j, b] <= sum(y[i, j] for i in s.Ib[b])\n",
    "                  for j in range(J) for b in range(B))\n",
    "    OP.addConstrs(d[j][b] >= s.rib[i][b] * y[i, j] for j in range(J)\n",
    "                  for b in range(B) for i in s.Ib[b])\n",
    "\n",
    "    OP.Params.timelimit = timebound  #设定求解器运行时间上限 单位为秒\n",
    "    OP.Params.LogToConsole = 0\n",
    "    FileStr = './Log/' + 'Direct_MIP_Return_solver' + '_' + str(s.number_of_order) + '_' + 'order' + '_' + str(s.number_of_batch) + '_' + 'batch' + '.log'\n",
    "    OP.Params.LogFile = FileStr\n",
    "\n",
    "    # Solve\n",
    "\n",
    "    OP.update()  #更新模型\n",
    "    OP.optimize()  #开始求解\n",
    "    OP.setParam(\"SolutionNumber\",0)\n",
    "    vy=OP.getAttr(\"xn\",y)\n",
    "    matrix=[[] for j in range(J)]\n",
    "    for j in range(J):\n",
    "        matrix[j].extend([i for i,x in enumerate(vy.select('*',j)) if x>0.5])\n",
    "    s.Direct_MIP_Return_matrix=matrix\n",
    "    return OP.ObjVal,OP.MIPGap"
   ]
  }
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