private LAPAssignment(LAPAssignment original, Cloner cloner) : base(original, cloner) { costs = cloner.Clone(original.costs); assignment = cloner.Clone(original.assignment); rowNames = cloner.Clone(original.rowNames); columnNames = cloner.Clone(original.columnNames); quality = cloner.Clone(original.quality); }
public override IOperation Apply() { var costs = CostsParameter.ActualValue; var rowNames = RowNamesParameter.ActualValue; var columnNames = ColumnNamesParameter.ActualValue; var permutations = AssignmentParameter.ActualValue; var qualities = QualityParameter.ActualValue; var results = ResultsParameter.ActualValue; bool max = MaximizationParameter.ActualValue.Value; DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue; var sorted = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).ToArray(); if (max) { sorted = sorted.Reverse().ToArray(); } int i = sorted.First().index; if (bestKnownQuality == null || max && qualities[i].Value > bestKnownQuality.Value || !max && qualities[i].Value < bestKnownQuality.Value) { // if there isn't a best-known quality or we improved the best-known quality we'll add the current solution as best-known BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[i].Value); BestKnownSolutionParameter.ActualValue = (Permutation)permutations[i].Clone(); BestKnownSolutionsParameter.ActualValue = new ItemSet <Permutation>(new PermutationEqualityComparer()); BestKnownSolutionsParameter.ActualValue.Add((Permutation)permutations[i].Clone()); } else if (bestKnownQuality.Value == qualities[i].Value) { // if we matched the best-known quality we'll try to set the best-known solution if it isn't null // and try to add it to the pool of best solutions if it is different if (BestKnownSolutionParameter.ActualValue == null) { BestKnownSolutionParameter.ActualValue = (Permutation)permutations[i].Clone(); } if (BestKnownSolutionsParameter.ActualValue == null) { BestKnownSolutionsParameter.ActualValue = new ItemSet <Permutation>(new PermutationEqualityComparer()); } foreach (var k in sorted) // for each solution that we found check if it is in the pool of best-knowns { if (!max && k.Value > qualities[i].Value || max && k.Value < qualities[i].Value) { break; // stop when we reached a solution worse than the best-known quality } Permutation p = permutations[k.index]; if (!BestKnownSolutionsParameter.ActualValue.Contains(p)) { BestKnownSolutionsParameter.ActualValue.Add((Permutation)permutations[k.index].Clone()); } } } LAPAssignment assignment = BestSolutionParameter.ActualValue; if (assignment == null) { assignment = new LAPAssignment(costs, rowNames, columnNames, (Permutation)permutations[i].Clone(), new DoubleValue(qualities[i].Value)); BestSolutionParameter.ActualValue = assignment; results.Add(new Result("Best LAP Solution", assignment)); } else { if (max && assignment.Quality.Value < qualities[i].Value || !max && assignment.Quality.Value > qualities[i].Value) { assignment.Costs = costs; assignment.Assignment = (Permutation)permutations[i].Clone(); assignment.Quality.Value = qualities[i].Value; if (rowNames != null) { assignment.RowNames = rowNames; } else { assignment.RowNames = null; } if (columnNames != null) { assignment.ColumnNames = columnNames; } else { assignment.ColumnNames = null; } } } return(base.Apply()); }
private LAPAssignment(LAPAssignment original, Cloner cloner) : base(original, cloner) { costs = cloner.Clone(original.costs); assignment = cloner.Clone(original.assignment); rowNames = cloner.Clone(original.rowNames); columnNames = cloner.Clone(original.columnNames); quality = cloner.Clone(original.quality); }
public override IOperation Apply() { var costs = CostsParameter.ActualValue; var rowNames = RowNamesParameter.ActualValue; var columnNames = ColumnNamesParameter.ActualValue; var permutations = AssignmentParameter.ActualValue; var qualities = QualityParameter.ActualValue; var results = ResultsParameter.ActualValue; bool max = MaximizationParameter.ActualValue.Value; DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue; var sorted = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).ToArray(); if (max) sorted = sorted.Reverse().ToArray(); int i = sorted.First().index; if (bestKnownQuality == null || max && qualities[i].Value > bestKnownQuality.Value || !max && qualities[i].Value < bestKnownQuality.Value) { // if there isn't a best-known quality or we improved the best-known quality we'll add the current solution as best-known BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[i].Value); BestKnownSolutionParameter.ActualValue = (Permutation)permutations[i].Clone(); BestKnownSolutionsParameter.ActualValue = new ItemSet<Permutation>(new PermutationEqualityComparer()); BestKnownSolutionsParameter.ActualValue.Add((Permutation)permutations[i].Clone()); } else if (bestKnownQuality.Value == qualities[i].Value) { // if we matched the best-known quality we'll try to set the best-known solution if it isn't null // and try to add it to the pool of best solutions if it is different if (BestKnownSolutionParameter.ActualValue == null) BestKnownSolutionParameter.ActualValue = (Permutation)permutations[i].Clone(); if (BestKnownSolutionsParameter.ActualValue == null) BestKnownSolutionsParameter.ActualValue = new ItemSet<Permutation>(new PermutationEqualityComparer()); foreach (var k in sorted) { // for each solution that we found check if it is in the pool of best-knowns if (!max && k.Value > qualities[i].Value || max && k.Value < qualities[i].Value) break; // stop when we reached a solution worse than the best-known quality Permutation p = permutations[k.index]; if (!BestKnownSolutionsParameter.ActualValue.Contains(p)) BestKnownSolutionsParameter.ActualValue.Add((Permutation)permutations[k.index].Clone()); } } LAPAssignment assignment = BestSolutionParameter.ActualValue; if (assignment == null) { assignment = new LAPAssignment(costs, rowNames, columnNames, (Permutation)permutations[i].Clone(), new DoubleValue(qualities[i].Value)); BestSolutionParameter.ActualValue = assignment; results.Add(new Result("Best LAP Solution", assignment)); } else { if (max && assignment.Quality.Value < qualities[i].Value || !max && assignment.Quality.Value > qualities[i].Value) { assignment.Costs = costs; assignment.Assignment = (Permutation)permutations[i].Clone(); assignment.Quality.Value = qualities[i].Value; if (rowNames != null) assignment.RowNames = rowNames; else assignment.RowNames = null; if (columnNames != null) assignment.ColumnNames = columnNames; else assignment.ColumnNames = null; } } return base.Apply(); }