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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.

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<?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>




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