117 lines
4.3 KiB
Plaintext
117 lines
4.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Copyright 2010-2018 Google LLC\n",
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"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
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"#\n",
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"# http://www.apache.org/licenses/LICENSE-2.0\n",
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"#\n",
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"# Unless required by applicable law or agreed to in writing, software\n",
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"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"# See the License for the specific language governing permissions and\n",
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"# limitations under the License.\n",
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"\"\"\"MIP example that uses a variable array.\"\"\"\n",
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"# [START program]\n",
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"# [START import]\n",
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"from __future__ import print_function\n",
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"from ortools.linear_solver import pywraplp\n",
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"\n",
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"# [END import]\n",
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"\n",
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"\n",
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"# [START program_part1]\n",
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"# [START data_model]\n",
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"def create_data_model():\n",
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" \"\"\"Stores the data for the problem.\"\"\"\n",
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" data = {}\n",
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" data['constraint_coeffs'] = [\n",
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" [5, 7, 9, 2, 1],\n",
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" [18, 4, -9, 10, 12],\n",
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" [4, 7, 3, 8, 5],\n",
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" [5, 13, 16, 3, -7],\n",
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" ]\n",
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" data['bounds'] = [250, 285, 211, 315]\n",
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" data['obj_coeffs'] = [7, 8, 2, 9, 6]\n",
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" data['num_vars'] = 5\n",
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" data['num_constraints'] = 4\n",
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" return data\n",
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"\n",
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"\n",
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"# [END data_model]\n",
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"\n",
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"\n",
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"# [START data]\n",
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"data = create_data_model()\n",
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"# [END data]\n",
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"# [END program_part1]\n",
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"# [START solver]\n",
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"# Create the mip solver with the CBC backend.\n",
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"solver = pywraplp.Solver('simple_mip_program',\n",
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" pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)\n",
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"# [END solver]\n",
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"\n",
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"# [START program_part2]\n",
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"# [START variables]\n",
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"infinity = solver.infinity()\n",
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"x = {}\n",
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"for j in range(data['num_vars']):\n",
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" x[j] = solver.IntVar(0, infinity, 'x[%i]' % j)\n",
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"print('Number of variables =', solver.NumVariables())\n",
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"# [END variables]\n",
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"\n",
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"# [START constraints]\n",
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"for i in range(data['num_constraints']):\n",
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" constraint = solver.RowConstraint(0, data['bounds'][i], '')\n",
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" for j in range(data['num_vars']):\n",
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" constraint.SetCoefficient(x[j], data['constraint_coeffs'][i][j])\n",
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"print('Number of constraints =', solver.NumConstraints())\n",
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"# In Python, you can also set the constraints as follows.\n",
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"# for i in range(data['num_constraints']):\n",
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"# constraint_expr = \\\n",
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"# [data['constraint_coeffs'][i][j] * x[j] for j in range(data['num_vars'])]\n",
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"# solver.Add(sum(constraint_expr) <= data['bounds'][i])\n",
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"# [END constraints]\n",
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"\n",
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"# [START objective]\n",
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"objective = solver.Objective()\n",
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"for j in range(data['num_vars']):\n",
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" objective.SetCoefficient(x[j], data['obj_coeffs'][j])\n",
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"objective.SetMaximization()\n",
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"# In Python, you can also set the objective as follows.\n",
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"# obj_expr = [data['obj_coeffs'][j] * x[j] for j in range(data['num_vars'])]\n",
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"# solver.Maximize(solver.Sum(obj_expr))\n",
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"# [END objective]\n",
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"\n",
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"# [START solve]\n",
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"status = solver.Solve()\n",
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"# [END solve]\n",
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"\n",
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"# [START print_solution]\n",
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"if status == pywraplp.Solver.OPTIMAL:\n",
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" print('Objective value =', solver.Objective().Value())\n",
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" for j in range(data['num_vars']):\n",
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" print(x[j].name(), ' = ', x[j].solution_value())\n",
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" print()\n",
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" print('Problem solved in %f milliseconds' % solver.wall_time())\n",
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" print('Problem solved in %d iterations' % solver.iterations())\n",
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" print('Problem solved in %d branch-and-bound nodes' % solver.nodes())\n",
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"else:\n",
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" print('The problem does not have an optimal solution.')\n",
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"# [END print_solution]\n",
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"\n"
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]
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}
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],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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