Java IloLinearNumExpr.setConstant方法代码示例

import ilog.concert.IloLinearNumExpr; //导入方法依赖的package包/类
private void addObjectiveCostSecondRoll() throws IloException {
	for (int firstRoll1 = 1; firstRoll1 <= numSides; firstRoll1++) {
	for (int secondRoll1 = 1; secondRoll1 <= numSides; secondRoll1++) {
	for (int firstRoll2 = 1; firstRoll2 <= numSides; firstRoll2++) {
	for (int secondRoll2 = 1; secondRoll2 <= numSides; secondRoll2++) {
		double cost = computeCostOfAbstractingSecondRollPair(firstRoll1, firstRoll2, secondRoll1, secondRoll2);
		for (int bucket = 0; bucket < numAbstractionInformationSets; bucket++) {
		
			//objective.addTerm(cost, secondRollAbstractionVariables[firstRoll1][secondRoll1][bucket]);
			IloLinearNumExpr expr = cplex.linearNumExpr();
			expr.addTerm(cost, secondRollAbstractionVariables[firstRoll1][secondRoll1][bucket]);
			expr.addTerm(cost, secondRollAbstractionVariables[firstRoll2][secondRoll2][bucket]);
			expr.setConstant(-cost);
			cplex.addLe(expr, costVariablesSecondRoll[firstRoll1][secondRoll1]);
			cplex.addLe(expr, costVariablesSecondRoll[firstRoll2][secondRoll2]);
		}
	}}}}		
}
 

import ilog.concert.IloLinearNumExpr; //导入方法依赖的package包/类
private IloLinearNumExpr getIncentivizedActionExpression(int informationSetId, Action incentivizedAction) throws IloException {
	IloLinearNumExpr actionExpr = cplex.linearNumExpr(); 
	int sequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, incentivizedAction.getName());
	
	// Iterate over nodes in information set
	double maxHeuristicAtNode = 0;
	TIntObjectMap<HashMap<String, IloNumVar>> exprMap = new TIntObjectHashMap<HashMap<String, IloNumVar>>();
	TIntArrayList informationSet = game.getInformationSet(playerNotToSolveFor, informationSetId);
	
	//IloNumVar actionValueVar = cplex.numVar(-Double.MAX_VALUE, Double.MAX_VALUE, "IncActionValue;"+Integer.toString(informationSetId) + incentivizedAction.getName());
	//actionExpr.addTerm(1, actionValueVar);

	for (int i = 0; i < informationSet.size(); i++) {
		Node node = game.getNodeById(informationSet.get(i));
		// ensure that we are using the correct Action at the node, so we can pull the correct childId
		Action incentiveActionForNode = node.getActions()[0];
		for (Action action : node.getActions()) {
			if (action.getName().equals(incentivizedAction.getName())) incentiveActionForNode = action;
		}
		IloNumVar actionActiveVar = cplex.boolVar("ActionActive" + Integer.toString(informationSetId) + incentivizedAction.getName());
		IloLinearNumExpr notDeactivatedExpr = cplex.linearNumExpr();
		notDeactivatedExpr.addTerm(-1, sequenceDeactivationVars[sequenceId]);
		notDeactivatedExpr.setConstant(1);
		cplex.addEq(actionActiveVar, notDeactivatedExpr, "NotDeactivated");
		fillIncentivizedActionExpression(actionExpr, actionActiveVar, incentiveActionForNode.getChildId(), exprMap, 1, Integer.toString(informationSetId) + incentivizedAction.getName());
		if (maxEvaluationValueForSequence[sequenceId] > maxHeuristicAtNode) {
			maxHeuristicAtNode = maxEvaluationValueForSequence[sequenceId];
		}
	}
	
	return actionExpr;
}
 

import ilog.concert.IloLinearNumExpr; //导入方法依赖的package包/类
private IloLinearNumExpr getIncentivizedActionExpression(int informationSetId, Action incentivizedAction) throws IloException {
    IloLinearNumExpr actionExpr = cplex.linearNumExpr();
    int sequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, incentivizedAction.getName());

    // Iterate over nodes in information set
    double maxHeuristicAtNode = 0;
    TIntObjectMap<HashMap<String, IloNumVar>> exprMap = new TIntObjectHashMap<HashMap<String, IloNumVar>>();
    TIntArrayList informationSet = game.getInformationSet(playerNotToSolveFor, informationSetId);

    //IloNumVar actionValueVar = cplex.numVar(-Double.MAX_VALUE, Double.MAX_VALUE, "IncActionValue;"+Integer.toString(informationSetId) + incentivizedAction.getName());
    //actionExpr.addTerm(1, actionValueVar);

    for (int i = 0; i < informationSet.size(); i++) {
        Node node = game.getNodeById(informationSet.get(i));
        // ensure that we are using the correct Action at the node, so we can pull the correct childId
        Action incentiveActionForNode = node.getActions()[0];
        for (Action action : node.getActions()) {
            if (action.getName().equals(incentivizedAction.getName())) incentiveActionForNode = action;
        }
        IloNumVar actionActiveVar = cplex.boolVar("ActionActive" + Integer.toString(informationSetId) + incentivizedAction.getName());
        IloLinearNumExpr notDeactivatedExpr = cplex.linearNumExpr();
        notDeactivatedExpr.addTerm(-1, sequenceDeactivationVars[sequenceId]);
        notDeactivatedExpr.setConstant(1);
        cplex.addEq(actionActiveVar, notDeactivatedExpr, "NotDeactivated");
        fillIncentivizedActionExpression(actionExpr, actionActiveVar, incentiveActionForNode.getChildId(), exprMap, 1, Integer.toString(informationSetId) + incentivizedAction.getName());
        if (maxEvaluationValueForSequence[sequenceId] > maxHeuristicAtNode) {
            maxHeuristicAtNode = maxEvaluationValueForSequence[sequenceId];
        }
    }

    return actionExpr;
}
 

import ilog.concert.IloLinearNumExpr; //导入方法依赖的package包/类
/**
 * Outer method that loops over all informationSetIds and action pairs for the limited look-ahead player.
 * @throws IloException
 */
private void addPrimalIncentiveConstraints() throws IloException {
	for (int informationSetId = game.getSmallestInformationSetId(playerNotToSolveFor); informationSetId < (numDualInformationSets + game.getSmallestInformationSetId(playerNotToSolveFor)); informationSetId++) {
		// We need to access the set of actions available at the information set. To do this, we loop over node.actions on the (arbitrarily picked) first node in the information set.
		int idOfFirstNodeInSet = game.getInformationSet(playerNotToSolveFor, informationSetId).get(0);
		Node firstNodeInSet = game.getNodeById(idOfFirstNodeInSet);
		// Dynamic programming table for expressions representing dominated actions
		HashMap<Action, IloLinearNumExpr> dominatedActionExpressionTable = new HashMap<Action, IloLinearNumExpr>();
		for (Action incentivizedAction : firstNodeInSet.getActions()) {
			// get expr representing value of chosen action
			IloLinearNumExpr incentiveExpr = getIncentivizedActionExpression(informationSetId, incentivizedAction);
			
			IloLinearNumExpr incentiveConstraintLHS = cplex.linearNumExpr();
			incentiveConstraintLHS.add(incentiveExpr);
			
			int incentiveSequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, incentivizedAction.getName());
			// ensure that expression is only active if the sequence is chosen
			//incentiveConstraintLHS.addTerm(maxEvaluationValueForSequence[incentiveSequenceId]+this.epsilon, sequenceDeactivationVars[incentiveSequenceId]);
	
			
			for (Action dominatedAction : firstNodeInSet.getActions()) {
				if (!incentivizedAction.equals(dominatedAction)) {
					// get expr representing value of dominated action
					IloLinearNumExpr dominatedExpr = getDominatedActionExpression(informationSetId, dominatedAction, dominatedActionExpressionTable);
					IloLinearNumExpr incentiveConstraintRHS = cplex.linearNumExpr();
					incentiveConstraintRHS.add(dominatedExpr);
					
					int dominatedSequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, dominatedAction.getName());
					// ensure that expression is only active is the sequence is deactivated
					incentiveConstraintRHS.addTerm(maxEvaluationValueForSequence[dominatedSequenceId]+this.epsilon, sequenceDeactivationVars[dominatedSequenceId]);
					incentiveConstraintRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[incentiveSequenceId]);
					// TODO: something needs to be flipped here. Perhaps it needs to be LB of other side
					incentiveConstraintRHS.setConstant(-maxEvaluationValueForSequence[dominatedSequenceId]);
					cplex.addGe(incentiveConstraintLHS, incentiveConstraintRHS, "PrimalIncentive("+informationSetId+";"+incentivizedAction.getName()+";"+dominatedAction.getName()+")");
					
					// add constraint requiring equality if both sequences are chosen to be incentivized, here we add one side of the two weak inequalities enforcing equality, since the other direction is also iterated over
					IloLinearNumExpr equalityRHS = cplex.linearNumExpr();
					equalityRHS.add(dominatedExpr);
					equalityRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[dominatedSequenceId]);
					equalityRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[incentiveSequenceId]);
					cplex.addGe(incentiveExpr, equalityRHS, "quality("+informationSetId+";"+incentivizedAction.getName()+";"+dominatedAction.getName()+")");
				}
			}
		}
	}
}
 

import ilog.concert.IloLinearNumExpr; //导入方法依赖的package包/类
/**
 * Outer method that loops over all informationSetIds and action pairs for the limited look-ahead player.
 * @throws IloException
 */
private void addPrimalIncentiveConstraints() throws IloException {
    for (int informationSetId = game.getSmallestInformationSetId(playerNotToSolveFor); informationSetId < (numDualInformationSets + game.getSmallestInformationSetId(playerNotToSolveFor)); informationSetId++) {
        // We need to access the set of actions available at the information set. To do this, we loop over node.actions on the (arbitrarily picked) first node in the information set.
        int idOfFirstNodeInSet = game.getInformationSet(playerNotToSolveFor, informationSetId).get(0);
        Node firstNodeInSet = game.getNodeById(idOfFirstNodeInSet);
        // Dynamic programming table for expressions representing dominated actions
        HashMap<Action, IloLinearNumExpr> dominatedActionExpressionTable = new HashMap<Action, IloLinearNumExpr>();
        for (Action incentivizedAction : firstNodeInSet.getActions()) {
            // get expr representing value of chosen action
            IloLinearNumExpr incentiveExpr = getIncentivizedActionExpression(informationSetId, incentivizedAction);

            IloLinearNumExpr incentiveConstraintLHS = cplex.linearNumExpr();
            incentiveConstraintLHS.add(incentiveExpr);

            int incentiveSequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, incentivizedAction.getName());
            // ensure that expression is only active if the sequence is chosen
            //incentiveConstraintLHS.addTerm(maxEvaluationValueForSequence[incentiveSequenceId]+this.epsilon, sequenceDeactivationVars[incentiveSequenceId]);


            for (Action dominatedAction : firstNodeInSet.getActions()) {
                if (!incentivizedAction.equals(dominatedAction)) {
                    // get expr representing value of dominated action
                    IloLinearNumExpr dominatedExpr = getDominatedActionExpression(informationSetId, dominatedAction, dominatedActionExpressionTable);
                    IloLinearNumExpr incentiveConstraintRHS = cplex.linearNumExpr();
                    incentiveConstraintRHS.add(dominatedExpr);

                    int dominatedSequenceId = getSequenceIdForPlayerNotToSolveFor(informationSetId, dominatedAction.getName());
                    // ensure that expression is only active is the sequence is deactivated
                    incentiveConstraintRHS.addTerm(maxEvaluationValueForSequence[dominatedSequenceId]+this.epsilon, sequenceDeactivationVars[dominatedSequenceId]);
                    incentiveConstraintRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[incentiveSequenceId]);
                    // TODO: something needs to be flipped here. Perhaps it needs to be LB of other side
                    incentiveConstraintRHS.setConstant(-maxEvaluationValueForSequence[dominatedSequenceId]);
                    cplex.addGe(incentiveConstraintLHS, incentiveConstraintRHS, "PrimalIncentive("+informationSetId+";"+incentivizedAction.getName()+";"+dominatedAction.getName()+")");

                    // add constraint requiring equality if both sequences are chosen to be incentivized, here we add one side of the two weak inequalities enforcing equality, since the other direction is also iterated over
                    IloLinearNumExpr equalityRHS = cplex.linearNumExpr();
                    equalityRHS.add(dominatedExpr);
                    equalityRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[dominatedSequenceId]);
                    equalityRHS.addTerm(-maxEvaluationValueForSequence[dominatedSequenceId], sequenceDeactivationVars[incentiveSequenceId]);
                    cplex.addGe(incentiveExpr, equalityRHS, "quality("+informationSetId+";"+incentivizedAction.getName()+";"+dominatedAction.getName()+")");
                }
            }
        }
    }
}