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OptaPlanner solves planning problems.
This lightweight, embeddable planning engine implements powerful and scalable algorithms
to optimize business resource scheduling and planning.
This module contains the examples which demonstrate how to use it in a normal Java application.
<?xml version="1.0" encoding="UTF-8"?> <plannerBenchmark xmlns="https://www.optaplanner.org/xsd/benchmark" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="https://www.optaplanner.org/xsd/benchmark https://www.optaplanner.org/xsd/benchmark/benchmark.xsd"> <benchmarkDirectory>local/data/nqueens</benchmarkDirectory> <parallelBenchmarkCount>AUTO</parallelBenchmarkCount> <inheritedSolverBenchmark> <solver> <solutionClass>org.optaplanner.examples.nqueens.domain.NQueens</solutionClass> <entityClass>org.optaplanner.examples.nqueens.domain.Queen</entityClass> <scoreDirectorFactory> <constraintProviderClass>org.optaplanner.examples.nqueens.score.NQueensConstraintProvider</constraintProviderClass> <initializingScoreTrend>ONLY_DOWN</initializingScoreTrend> </scoreDirectorFactory> <termination> <terminationCompositionStyle>OR</terminationCompositionStyle> <secondsSpentLimit>20</secondsSpentLimit> <bestScoreLimit>0</bestScoreLimit> </termination> </solver> <problemBenchmarks> <solutionFileIOClass>org.optaplanner.examples.nqueens.persistence.NQueensSolutionFileIO</solutionFileIOClass> <writeOutputSolutionEnabled>true</writeOutputSolutionEnabled> <inputSolutionFile>data/nqueens/unsolved/32queens.json</inputSolutionFile> <inputSolutionFile>data/nqueens/unsolved/64queens.json</inputSolutionFile> <!--<problemStatisticType>BEST_SCORE</problemStatisticType>--> <!--<problemStatisticType>STEP_SCORE</problemStatisticType>--> <!--<problemStatisticType>SCORE_CALCULATION_SPEED</problemStatisticType>--> <!--<problemStatisticType>BEST_SOLUTION_MUTATION</problemStatisticType>--> <!--<problemStatisticType>MOVE_COUNT_PER_STEP</problemStatisticType>--> <!--<problemStatisticType>MEMORY_USE</problemStatisticType>--> <!--<singleStatisticType>CONSTRAINT_MATCH_TOTAL_BEST_SCORE</singleStatisticType>--> <!--<singleStatisticType>CONSTRAINT_MATCH_TOTAL_STEP_SCORE</singleStatisticType>--> <!--<singleStatisticType>PICKED_MOVE_TYPE_BEST_SCORE_DIFF</singleStatisticType>--> <!--<singleStatisticType>PICKED_MOVE_TYPE_STEP_SCORE_DIFF</singleStatisticType>--> </problemBenchmarks> </inheritedSolverBenchmark> <solverBenchmark> <name>First Fit</name> <solver> <constructionHeuristic> <constructionHeuristicType>FIRST_FIT</constructionHeuristicType> </constructionHeuristic> </solver> </solverBenchmark> <solverBenchmark> <name>First Fit Decreasing</name> <solver> <constructionHeuristic> <constructionHeuristicType>FIRST_FIT_DECREASING</constructionHeuristicType> </constructionHeuristic> </solver> </solverBenchmark> <solverBenchmark> <name>Weakest Fit</name> <solver> <constructionHeuristic> <constructionHeuristicType>WEAKEST_FIT</constructionHeuristicType> </constructionHeuristic> </solver> </solverBenchmark> <solverBenchmark> <name>Weakest Fit Decreasing</name> <solver> <constructionHeuristic> <constructionHeuristicType>WEAKEST_FIT_DECREASING</constructionHeuristicType> </constructionHeuristic> </solver> </solverBenchmark> <solverBenchmark> <name>Entity Tabu Search</name> <solver> <constructionHeuristic> <constructionHeuristicType>FIRST_FIT_DECREASING</constructionHeuristicType> </constructionHeuristic> <localSearch> <changeMoveSelector> <selectionOrder>ORIGINAL</selectionOrder> </changeMoveSelector> <acceptor> <entityTabuSize>5</entityTabuSize> </acceptor> <forager> </forager> </localSearch> </solver> </solverBenchmark> </plannerBenchmark>