Add missing basic examples
C++: - [Up] linear_programming - [Up] integer_programming - constraint_programming_CP / rabbits_pheasants_cp - knapsack - max_flow / min_cost_flow - tsp / vrp note: previous "fuzzy" tsp has been renamed random_tsp. .Net: - vrp
This commit is contained in:
Corentin Le Molgat
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examples/dotnet/vrp.cs
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164
examples/dotnet/vrp.cs
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// Copyright 2018 Google
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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using System;
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using System.Collections.Generic;
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using Google.OrTools.ConstraintSolver;
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/// <summary>
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/// This is a sample using the routing library .Net wrapper to solve a VRP problem.
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/// A description of the problem can be found here:
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/// http://en.wikipedia.org/wiki/Vehicle_routing_problem.
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/// </summary>
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public class VRP {
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class DataProblem {
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private int[,] locations_;
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// Constructor:
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public DataProblem() {
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locations_ = new int[,] {
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{4, 4},
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{2, 0}, {8, 0},
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{0, 1}, {1, 1},
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{5, 2}, {7, 2},
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{3, 3}, {6, 3},
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{5, 5}, {8, 5},
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{1, 6}, {2, 6},
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{3, 7}, {6, 7},
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{0, 8}, {7, 8}
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};
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// Compute locations in meters using the block dimension defined as follow
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// Manhattan average block: 750ft x 264ft -> 228m x 80m
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// here we use: 114m x 80m city block
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// src: https://nyti.ms/2GDoRIe "NY Times: Know Your distance"
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int[] cityBlock = {228/2, 80};
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for (int i=0; i < locations_.GetLength(0); i++) {
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locations_[i, 0] = locations_[i, 0] * cityBlock[0];
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locations_[i, 1] = locations_[i, 1] * cityBlock[1];
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}
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}
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public int GetVehicleNumber() { return 4;}
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public ref readonly int[,] GetLocations() { return ref locations_;}
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public int GetLocationNumber() { return locations_.GetLength(0);}
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public int GetDepot() { return 0;}
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};
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/// <summary>
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/// Manhattan distance implemented as a callback. It uses an array of
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/// positions and computes the Manhattan distance between the two
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/// positions of two different indices.
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/// </summary>
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class ManhattanDistance : NodeEvaluator2 {
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private int[,] distances_;
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public ManhattanDistance(in DataProblem data) {
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// precompute distance between location to have distance callback in O(1)
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distances_ = new int[data.GetLocationNumber(), data.GetLocationNumber()];
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for (int fromNode = 0; fromNode < data.GetLocationNumber(); fromNode++) {
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for (int toNode = 0; toNode < data.GetLocationNumber(); toNode++) {
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if (fromNode == toNode)
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distances_[fromNode, toNode] = 0;
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else
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distances_[fromNode, toNode] =
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Math.Abs(data.GetLocations()[toNode, 0] - data.GetLocations()[fromNode, 0]) +
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Math.Abs(data.GetLocations()[toNode, 1] - data.GetLocations()[fromNode, 1]);
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}
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}
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}
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/// <summary>
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/// Returns the manhattan distance between the two nodes
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/// </summary>
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public override long Run(int FromNode, int ToNode) {
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return distances_[FromNode, ToNode];
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}
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};
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/// <summary>
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/// Add distance Dimension
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/// </summary>
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static void AddDistanceDimension(
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in DataProblem data,
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in RoutingModel routing) {
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String distance = "Distance";
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routing.AddDimension(
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new ManhattanDistance(data),
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0, // null slack
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3000, // maximum distance per vehicle
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true, // start cumul to zero
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distance);
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RoutingDimension distanceDimension = routing.GetDimensionOrDie(distance);
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// Try to minimize the max distance among vehicles.
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// /!\ It doesn't mean the standard deviation is minimized
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distanceDimension.SetGlobalSpanCostCoefficient(100);
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}
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/// <summary>
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/// Print the solution
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/// </summary>
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static void PrintSolution(
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in DataProblem data,
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in RoutingModel routing,
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in Assignment solution) {
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Console.WriteLine("Objective: {0}", solution.ObjectiveValue());
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// Inspect solution.
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for (int i=0; i < data.GetVehicleNumber(); ++i) {
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Console.WriteLine("Route for Vehicle " + i + ":");
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long distance = 0;
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var index = routing.Start(i);
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while (routing.IsEnd(index) == false) {
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Console.Write("{0} -> ", routing.IndexToNode(index));
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var previousIndex = index;
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index = solution.Value(routing.NextVar(index));
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distance += routing.GetArcCostForVehicle(previousIndex, index, i);
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}
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Console.WriteLine("{0}", routing.IndexToNode(index));
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Console.WriteLine("Distance of the route: {0}m", distance);
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}
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}
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/// <summary>
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/// Solves the current routing problem.
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/// </summary>
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static void Solve() {
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// Instantiate the data problem.
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DataProblem data = new DataProblem();
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// Create Routing Model
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RoutingModel routing = new RoutingModel(
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data.GetLocationNumber(),
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data.GetVehicleNumber(),
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data.GetDepot());
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// Define weight cost of each edge
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NodeEvaluator2 distanceEvaluator = new ManhattanDistance(data);
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//protect callbacks from the GC
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GC.KeepAlive(distanceEvaluator);
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routing.SetArcCostEvaluatorOfAllVehicles(distanceEvaluator);
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AddDistanceDimension(data, routing);
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// Setting first solution heuristic (cheapest addition).
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RoutingSearchParameters searchParameters = RoutingModel.DefaultSearchParameters();
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searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
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Assignment solution = routing.SolveWithParameters(searchParameters);
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PrintSolution(data, routing, solution);
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}
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public static void Main(String[] args) {
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Solve();
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}
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}
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20
examples/dotnet/vrp.csproj
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20
examples/dotnet/vrp.csproj
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<LangVersion>7.2</LangVersion>
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<TargetFramework>netcoreapp2.1</TargetFramework>
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<EnableDefaultItems>false</EnableDefaultItems>
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<RestoreSources>../../packages;$(RestoreSources);https://api.nuget.org/v3/index.json</RestoreSources>
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</PropertyGroup>
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<PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
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<DebugType>full</DebugType>
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<Optimize>true</Optimize>
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<GenerateTailCalls>true</GenerateTailCalls>
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</PropertyGroup>
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<ItemGroup>
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<Compile Include="vrp.cs" />
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<PackageReference Include="Google.OrTools" Version="6.9.*" />
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</ItemGroup>
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</Project>
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