ForceInnovationStrategyChooser.java

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package org.matsim.core.replanning.choosers;

import org.matsim.api.core.v01.population.BasicPlan;
import org.matsim.api.core.v01.population.HasPlansAndId;
import org.matsim.core.gbl.MatsimRandom;
import org.matsim.core.replanning.GenericPlanStrategy;
import org.matsim.core.replanning.ReplanningContext;
import org.matsim.core.replanning.ReplanningUtils;

public class ForceInnovationStrategyChooser<PL extends BasicPlan, AG extends HasPlansAndId<? extends BasicPlan, AG>> implements StrategyChooser<PL, AG> {

    private final int iter;
    private final boolean permute;

    public ForceInnovationStrategyChooser(int iter, Permute permute) {
        this.iter = iter;
        this.permute = permute == Permute.yes;
    }

    static int hash(final int value) {
        int x = value;

        x = ((x >>> 16) ^ x) * 0x119de1f3;
        x = ((x >>> 16) ^ x) * 0x119de1f3;
        x = (x >>> 16) ^ x;

        return x;
    }

    @Override
    public GenericPlanStrategy<PL, AG> chooseStrategy(HasPlansAndId<PL, AG> person, String subpopulation, ReplanningContext replanningContext, Weights<PL, AG> weights) {

        double[] w = new double[weights.size()];
        double total = 0;

        // permutation term so the selection is different every nth iterations
        int perm = (replanningContext.getIteration() / iter) % 16;

        for (int i = 0; i < weights.size(); i++) {


            int term = (permute ? hash(person.getId().index()) >>> perm : person.getId().index()) % iter;
            int mod = replanningContext.getIteration() % iter;

            // Set selectors weight to zero, so only innovate strategies remain
            if ((term == mod || -term == mod) && ReplanningUtils.isOnlySelector(weights.getStrategy(i))) {
                w[i] = 0;
            } else
                w[i] = weights.getWeight(i);

            total += w[i];
        }

        double rnd = MatsimRandom.getRandom().nextDouble() * total;

        // If all weights are zero the first one is returned
        double sum = 0.0;
        for (int i = 0, max = weights.size(); i < max; i++) {
            sum += w[i];
            if (rnd <= sum) {
                return weights.getStrategy(i);
            }
        }
        return null;

    }

    public enum Permute {
        yes,
        no
    }

}