137 lines
3.9 KiB
C#
137 lines
3.9 KiB
C#
// Copyright 2010-2018 Google LLC
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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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// [START program]
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// [START import]
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using System;
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using Google.OrTools.LinearSolver;
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// [END import]
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// [START program_part1]
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public class BinPackingMip
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{
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// [START data_model]
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class DataModel
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{
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public double[] Weights = {48, 30, 19, 36, 36, 27, 42, 42, 36, 24, 30};
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public double[] BinCapacity = 100;
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public int NumItems = Weights.Length;
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public int NumBins = Weights.Length;
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}
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// [END data_model]
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public static void Main()
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{
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// [START data]
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DataModel data = new DataModel();
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// [END data]
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// [END program_part1]
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// [START solver]
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// Create the linear solver with the CBC backend.
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Solver solver = Solver.CreateSolver("BinPackingMip", "CBC_MIXED_INTEGER_PROGRAMMING");
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// [END solver]
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// [START program_part2]
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// [START variables]
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MPVariable[,] x = new MPVariable[data.NumItems][data.NumBins];
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for (int i = 0; i < data.NumItems; i++)
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{
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for (int j = 0; j < data.NumBins; j++)
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{
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x[i][j] = MakeIntVar(0, 1, String.Format("x_{0}_{1}", i, j));
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}
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}
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MPVariable[] y = new MPVariable[data.NumBins];
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for (int j = 0; j < data.NumBins; j++)
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{
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y[j] = MakeIntVar(0, 1, String.Format("y_{0}", j));
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}
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// [END variables]
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// [START constraints]
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for (int i = 0; i < data.NumItems; ++i) {
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LinearExpr sum;
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for (int j = 0; j < data.NumBins; ++j) {
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sum += x[i][j];
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}
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}
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solver.MakeRowConstraint(sum == 1.0);
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for (int i = 0; i < data.NumConstraints; ++i)
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{
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MPConstraint constraint = solver.MakeConstraint(0, data.Bounds[i], "");
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for (int j = 0; j < data.NumVars; ++j)
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{
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constraint.SetCoefficient(x[j], data.ConstraintCoeffs[i][j]);
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}
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}
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for (int j = 0; j < data.NumBins; ++j)
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{
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LinearExpr Weight;
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for (int i = 0; i < data.NumItems; ++i)
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{
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Weight += data.Weights[i]*LinearExpr(x[i][j]);
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}
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solver.MakeRowConstraint(Weight <= data.BinCapacities[j]);
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}
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// [END constraints]
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// [START objective]
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objective = solver.Objective();
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LinearExpr NumBinsUsed;
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for (int j = 0; j < data.NumBins; ++j)
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{
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NumBinsUsed += y[j];
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}
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}
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objective.MinimizeLinearExpr(NumBinsUsed);
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// [END objective]
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// [START solve]
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Solver.ResultStatus resultStatus = solver.Solve();
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// [END solve]
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// [START print_solution]
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// Check that the problem has an optimal solution.
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if (resultStatus != Solver.ResultStatus.OPTIMAL)
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{
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Console.WriteLine("The problem does not have an optimal solution!");
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return;
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}
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Console.WriteLine("Number of bins used: " + solver.Objective().Value());
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int TotalWeight = 0;
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for (int j = 0; j < data.NumBins; ++j)
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{
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int BinWeight = 0;
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if (y[j] == 1)
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{
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Console.WriteLine("Bin " + j);
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for (int i = 0; i < data.NumItems; ++i)
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{
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if (x[i][j].SolutionValue() == 1)
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{
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Console.WriteLine("Item " + i + " weight: " + data.Weights[i]
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+ " values: " + data.Values[i];
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BinWeight += data.Weights[i];
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}
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}
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Console.WriteLine("Packed bin weight: " + BinWeight);
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TotalWeight += BinWeight;
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}
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Console.WriteLine("Total packed weight: " + TotalWeight);
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// [END print_solution]
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}
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}
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}
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// [END program_part2]
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// [END program]
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