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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"?>
<solver>
  <!--<environmentMode>DEBUG</environmentMode>-->
  <solutionClass>org.drools.planner.examples.travelingtournament.domain.TravelingTournament</solutionClass>
  <planningEntityClass>org.drools.planner.examples.travelingtournament.domain.Match</planningEntityClass>

  <scoreDirectorFactory>
    <scoreDefinitionType>HARD_AND_SOFT</scoreDefinitionType>
    <scoreDrl>/org/drools/planner/examples/travelingtournament/solver/travelingTournamentScoreRules.drl</scoreDrl>
  </scoreDirectorFactory>

  <termination>
    <scoreAttained>0hard/0soft</scoreAttained>
  </termination>
  <localSearch>
    <unionMoveSelector>
      <swapMoveSelector>
        <cacheType>PHASE</cacheType>
        <selectionOrder>SHUFFLED</selectionOrder>
        <moveFilterClass>org.drools.planner.examples.travelingtournament.solver.move.factory.InverseMatchSwapMoveFilter</moveFilterClass>
      </swapMoveSelector>
      <moveListFactory>
        <cacheType>STEP</cacheType>
        <selectionOrder>SHUFFLED</selectionOrder>
        <moveListFactoryClass>org.drools.planner.examples.travelingtournament.solver.move.factory.MatchChainRotationsMoveFactory</moveListFactoryClass>
      </moveListFactory>
    </unionMoveSelector>
    <acceptor>
      <solutionTabuSize>1500</solutionTabuSize>
      <moveTabuSize>7</moveTabuSize>
    </acceptor>
    <forager>
      <deciderScoreComparatorFactory>
        <deciderScoreComparatorFactoryType>SHIFTING_HARD_PENALTY</deciderScoreComparatorFactoryType>
        <hardScoreActivationThreshold>0</hardScoreActivationThreshold>
        <successiveNoHardChangeMinimum>2</successiveNoHardChangeMinimum>
        <successiveNoHardChangeMaximum>20</successiveNoHardChangeMaximum>
        <successiveNoHardChangeRepetitionMultiplicand>20.0</successiveNoHardChangeRepetitionMultiplicand>
        <hardWeightSurvivalRatio>0.5</hardWeightSurvivalRatio>
        <startingHardWeight>1000</startingHardWeight>
      </deciderScoreComparatorFactory>
      <!-- Real world problems require to use of <minimalAcceptedSelection> -->
    </forager>
  </localSearch>
</solver>