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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"?> <solverBenchmarkSuite> <benchmarkDirectory>local/data/nurserostering</benchmarkDirectory> <solverStatisticType>BEST_SOLUTION_CHANGED</solverStatisticType> <inheritedUnsolvedSolutionFile>data/nurserostering/unsolved/medium_late01_initialized.xml</inheritedUnsolvedSolutionFile> <inheritedLocalSearchSolver> <!--<environmentMode>DEBUG</environmentMode>--> <scoreDrl>/org/drools/planner/examples/nurserostering/solver/nurseRosteringScoreRules.drl</scoreDrl> <scoreDefinition> <scoreDefinitionType>HARD_AND_SOFT</scoreDefinitionType> </scoreDefinition> <startingSolutionInitializerClass>org.drools.planner.examples.nurserostering.solver.solution.initializer.NurseRosteringStartingSolutionInitializer</startingSolutionInitializerClass> <termination> <maximumStepCount>100</maximumStepCount> </termination> </inheritedLocalSearchSolver> <solverBenchmark> <localSearchSolver> <selector> <selector> <moveFactoryClass>org.drools.planner.examples.nurserostering.solver.move.factory.EmployeeChangeMoveFactory</moveFactoryClass> </selector> <selector> <moveFactoryClass>org.drools.planner.examples.nurserostering.solver.move.factory.AssignmentSwitchMoveFactory</moveFactoryClass> </selector> </selector> <acceptor> <completeSolutionTabuSize>1000</completeSolutionTabuSize> <completeMoveTabuSize>7</completeMoveTabuSize> </acceptor> <forager> <pickEarlyType>NEVER</pickEarlyType> <minimalAcceptedSelection>1000</minimalAcceptedSelection> </forager> </localSearchSolver> </solverBenchmark> </solverBenchmarkSuite>