#region License Information /* HeuristicLab * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Diagnostics.Contracts; using System.IO; using System.Linq; using HeuristicLab.Core; using HeuristicLab.Problems.Instances; using HeuristicLab.Random; namespace HeuristicLab.Problems.BinPacking2D { // make sure that for each class we have a separate entry in the problem instance providers public class RandomInstanceClass1Provider : RandomInstanceProvider { public RandomInstanceClass1Provider() : base() { @class = 1; binWidth = binHeight = 10; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 11); h = rand.Next(1, 11); } } public class RandomInstanceClass2Provider : RandomInstanceProvider { public RandomInstanceClass2Provider() : base() { @class = 2; binWidth = binHeight = 30; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 11); h = rand.Next(1, 11); } } public class RandomInstanceClass3Provider : RandomInstanceProvider { public RandomInstanceClass3Provider() : base() { @class = 3; binWidth = binHeight = 40; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 36); h = rand.Next(1, 36); } } public class RandomInstanceClass4Provider : RandomInstanceProvider { public RandomInstanceClass4Provider() : base() { @class = 4; binWidth = binHeight = 100; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 36); h = rand.Next(1, 36); } } public class RandomInstanceClass5Provider : RandomInstanceProvider { public RandomInstanceClass5Provider() : base() { @class = 5; binWidth = binHeight = 100; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 101); h = rand.Next(1, 101); } } public class RandomInstanceClass6Provider : RandomInstanceProvider { public RandomInstanceClass6Provider() : base() { @class = 6; binWidth = binHeight = 300; } protected override void SampleItemParameters(IRandom rand, out int w, out int h) { w = rand.Next(1, 101); h = rand.Next(1, 101); } } public class RandomInstanceClass7Provider : RandomInstanceProvider { public RandomInstanceClass7Provider() : base() { @class = 7; binWidth = binHeight = 100; } } public class RandomInstanceClass8Provider : RandomInstanceProvider { public RandomInstanceClass8Provider() : base() { @class = 8; binWidth = binHeight = 100; } } public class RandomInstanceClass9Provider : RandomInstanceProvider { public RandomInstanceClass9Provider() : base() { @class = 9; binWidth = binHeight = 100; } } public class RandomInstanceClass10Provider : RandomInstanceProvider { public RandomInstanceClass10Provider() : base() { @class = 10; binWidth = binHeight = 100; } } public abstract class RandomInstanceProvider : ProblemInstanceProvider, IProblemInstanceProvider { protected int @class; protected int binWidth, binHeight; public override string Name { get { return string.Format("Lodi, Martelli, Vigo (class={0})", @class); } } public override string Description { get { return "Randomly generated 2d bin packing problems as described in Lodi, Martello, and Vigo. 'Heuristic and metaheuristic approaches for a class of two-dimensional bin packing problems.' INFORMS Journal on Computing 11.4 (1999): 345-357."; } } public override Uri WebLink { get { return null; } } public override string ReferencePublication { get { return "Lodi, Martello, and Vigo. 'Heuristic and metaheuristic approaches for a class of two-dimensional bin packing problems.' INFORMS Journal on Computing 11.4 (1999): 345-357."; } } public RandomInstanceProvider() : base() { } public override IEnumerable GetDataDescriptors() { // 10 classes var rand = new MersenneTwister(1234); // fixed seed to makes sure that instances are always the same foreach (int numItems in new int[] { 20, 40, 60, 80, 100 }) { // get class parameters // generate 30 different instances for each class foreach (int instance in Enumerable.Range(1, 30)) { string name = string.Format("n={0}-id={1:00} (class={2})", numItems, instance, @class); var dd = new RandomDataDescriptor(name, name, numItems, seed: rand.Next()); yield return dd; } } } public override BPPData LoadData(IDataDescriptor dd) { var randDd = dd as RandomDataDescriptor; if (randDd == null) throw new NotSupportedException("Cannot load data descriptor " + dd); var data = new BPPData() { BinShape = new PackingShape(binWidth, binHeight), Items = new PackingItem[randDd.NumItems] }; var instanceRand = new MersenneTwister((uint)randDd.Seed); for (int i = 0; i < randDd.NumItems; i++) { int w, h; SampleItemParameters(instanceRand, out w, out h); data.Items[i] = new PackingItem(w, h, data.BinShape); } return data; } // default implementation for class 7 .. 10 protected virtual void SampleItemParameters(IRandom rand, out int w, out int h) { // for classes 1 - 5 Contract.Assert(@class >= 7 && @class <= 10); var weights = new double[] { 0.1, 0.1, 0.1, 0.1 }; weights[@class - 7] = 0.7; var type = Enumerable.Range(1, 4).SampleProportional(rand, 1, weights).First(); int minW, maxW; int minH, maxH; GetItemParameters(type, rand, binWidth, binHeight, out minW, out maxW, out minH, out maxH); w = rand.Next(minW, maxW + 1); h = rand.Next(minH, maxH + 1); } private void GetItemParameters(int type, IRandom rand, int w, int h, out int minW, out int maxW, out int minH, out int maxH) { switch (type) { case 1: { minW = w * 2 / 3; maxW = w; // integer division on purpose (see paper) minH = 1; maxH = h / 2; break; } case 2: { minW = 1; maxW = w / 2; minH = h * 2 / 3; maxH = h; break; } case 3: { minW = w / 2; maxW = w; minH = h / 2; maxH = h; break; } case 4: { minW = 1; maxW = w / 2; minH = 1; maxH = h / 2; break; } default: { throw new InvalidProgramException(); } } } public override bool CanImportData { get { return false; } } public override BPPData ImportData(string path) { throw new NotSupportedException(); } public override bool CanExportData { get { return true; } } public override void ExportData(BPPData instance, string file) { using (Stream stream = new FileStream(file, FileMode.OpenOrCreate, FileAccess.Write)) { Export(instance, stream); } } public static void Export(BPPData instance, Stream stream) { using (var writer = new StreamWriter(stream)) { writer.WriteLine(String.Format("{0,-5} {1,-5} WBIN,HBIN", instance.BinShape.Width, instance.BinShape.Height)); for (int i = 0; i < instance.NumItems; i++) { if (i == 0) writer.WriteLine("{0,-5} {1,-5} W(I),H(I),I=1,...,N", instance.Items[i].Width, instance.Items[i].Height); else writer.WriteLine("{0,-5} {1,-5}", instance.Items[i].Width, instance.Items[i].Height); } writer.Flush(); } } } }