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Drools Planner optimizes automated planning by combining metaheuristic search algorithms with rule
engine powered score calculation. This is the drools-planner-examples module which contains examples on how to use
Drools Planner.
<?xml version="1.0" encoding="UTF-8"?> <plannerBenchmark> <benchmarkDirectory>local/data/nqueens/stepLimit</benchmarkDirectory> <inheritedSolverBenchmark> <problemBenchmarks> <xstreamAnnotatedClass>org.drools.planner.examples.nqueens.domain.NQueens</xstreamAnnotatedClass> <inputSolutionFile>data/nqueens/unsolved/unsolvedNQueens256.xml</inputSolutionFile> </problemBenchmarks> <solver> <solutionClass>org.drools.planner.examples.nqueens.domain.NQueens</solutionClass> <planningEntityClass>org.drools.planner.examples.nqueens.domain.Queen</planningEntityClass> <scoreDirectorFactory> <scoreDefinitionType>SIMPLE</scoreDefinitionType> <scoreDrl>/org/drools/planner/examples/nqueens/solver/nQueensScoreRules.drl</scoreDrl> </scoreDirectorFactory> </solver> </inheritedSolverBenchmark> <solverBenchmark> <name>Entity tabu</name> <solver> <constructionHeuristic> <constructionHeuristicType>FIRST_FIT_DECREASING</constructionHeuristicType> <constructionHeuristicPickEarlyType>FIRST_LAST_STEP_SCORE_EQUAL_OR_IMPROVING</constructionHeuristicPickEarlyType> </constructionHeuristic> <localSearch> <termination> <maximumStepCount>100</maximumStepCount> </termination> <changeMoveSelector> <selectionOrder>ORIGINAL</selectionOrder> </changeMoveSelector> <acceptor> <planningEntityTabuSize>5</planningEntityTabuSize> </acceptor> <forager> </forager> </localSearch> </solver> </solverBenchmark> </plannerBenchmark>