143 lines
4.0 KiB
Plaintext
143 lines
4.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "google",
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"metadata": {},
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"source": [
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"##### Copyright 2025 Google LLC."
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]
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},
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{
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"cell_type": "markdown",
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"id": "apache",
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"metadata": {},
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"source": [
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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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]
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},
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{
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"cell_type": "markdown",
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"id": "basename",
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"metadata": {},
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"source": [
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"# simple_mip_program_mb"
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]
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},
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{
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"cell_type": "markdown",
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"id": "link",
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"metadata": {},
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"source": [
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"<table align=\"left\">\n",
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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/linear_solver/simple_mip_program_mb.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
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"</td>\n",
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"<td>\n",
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"<a href=\"https://github.com/google/or-tools/blob/main/ortools/linear_solver/samples/simple_mip_program_mb.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
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"</td>\n",
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"</table>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "doc",
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"metadata": {},
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"source": [
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"First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "install",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install ortools"
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]
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},
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{
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"cell_type": "markdown",
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"id": "description",
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"metadata": {},
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"source": [
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"\n",
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"Integer programming examples that show how to use the APIs."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "code",
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"metadata": {},
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"outputs": [],
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"source": [
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"import math\n",
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"\n",
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"from ortools.linear_solver.python import model_builder\n",
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"\n",
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"\n",
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"def main():\n",
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" # Create the model.\n",
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" model = model_builder.Model()\n",
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"\n",
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" # x and y are integer non-negative variables.\n",
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" x = model.new_int_var(0.0, math.inf, \"x\")\n",
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" y = model.new_int_var(0.0, math.inf, \"y\")\n",
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"\n",
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" print(\"Number of variables =\", model.num_variables)\n",
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"\n",
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" # x + 7 * y <= 17.5.\n",
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" model.add(x + 7 * y <= 17.5)\n",
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"\n",
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" # x <= 3.5.\n",
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" model.add(x <= 3.5)\n",
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"\n",
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" print(\"Number of constraints =\", model.num_constraints)\n",
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"\n",
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" # Maximize x + 10 * y.\n",
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" model.maximize(x + 10 * y)\n",
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"\n",
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" # Create the solver with the SCIP backend, and solve the model.\n",
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" solver = model_builder.Solver(\"scip\")\n",
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" if not solver.solver_is_supported():\n",
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" return\n",
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" status = solver.solve(model)\n",
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"\n",
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" if status == model_builder.SolveStatus.OPTIMAL:\n",
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" print(\"Solution:\")\n",
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" print(\"Objective value =\", solver.objective_value)\n",
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" print(\"x =\", solver.value(x))\n",
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" print(\"y =\", solver.value(y))\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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"\n",
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" print(\"\\nAdvanced usage:\")\n",
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" print(\"Problem solved in %f seconds\" % solver.wall_time)\n",
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"\n",
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"\n",
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"main()\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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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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