Examples with CCIncrementalData org.logicng.cardinalityconstraints.CCIncrementalData used on opensource projects

Example 1 with CCIncrementalData

use of org.logicng.cardinalityconstraints.CCIncrementalData in project LogicNG by logic-ng.

the class QuineMcCluskeyAlgorithm method minimize.

/**
 * Performs the minimization via incremental cardinality constraints.
 * @param satSolver the SAT solver
 * @param var2Term  a mapping from selector variable to prime implicant
 * @param f         the formula factory
 * @return a minimal set of prime implicants to cover all minterms
 */
static List<Term> minimize(final SATSolver satSolver, final LinkedHashMap<Variable, Term> var2Term, final FormulaFactory f) {
    final Assignment initialModel = satSolver.model();
    List<Variable> currentTermVars = computeCurrentTermVars(initialModel, var2Term.keySet());
    if (currentTermVars.size() == 2) {
        satSolver.add(f.amo(var2Term.keySet()));
        if (satSolver.sat() == Tristate.TRUE) {
            currentTermVars = computeCurrentTermVars(satSolver.model(), var2Term.keySet());
        }
    } else {
        final Formula cc = f.cc(CType.LE, currentTermVars.size() - 1, var2Term.keySet());
        assert cc instanceof CardinalityConstraint;
        final CCIncrementalData incData = satSolver.addIncrementalCC((CardinalityConstraint) cc);
        while (satSolver.sat() == Tristate.TRUE) {
            currentTermVars = computeCurrentTermVars(satSolver.model(), var2Term.keySet());
            incData.newUpperBoundForSolver(currentTermVars.size() - 1);
        }
    }
    return computeTerms(currentTermVars, var2Term);
}

Example 2 with CCIncrementalData

use of org.logicng.cardinalityconstraints.CCIncrementalData in project LogicNG by logic-ng.

the class OptimizationFunction method maximize.

private Assignment maximize(final MiniSat solver) {
    start(this.handler);
    final FormulaFactory f = solver.factory();
    LNGBooleanVector internalModel;
    final Map<Variable, Literal> selectorMap = new TreeMap<>();
    for (final Literal lit : this.literals) {
        final Variable selVar = f.variable(SEL_PREFIX + selectorMap.size());
        selectorMap.put(selVar, lit);
    }
    final Set<Variable> selectors = selectorMap.keySet();
    if (this.maximize) {
        selectorMap.forEach((selVar, lit) -> solver.add(f.or(selVar.negate(), lit)));
        selectorMap.forEach((selVar, lit) -> solver.add(f.or(lit.negate(), selVar)));
    } else {
        selectorMap.forEach((selVar, lit) -> solver.add(f.or(selVar.negate(), lit.negate())));
        selectorMap.forEach((selVar, lit) -> solver.add(f.or(lit, selVar)));
    }
    Tristate sat = solver.sat(satHandler(handler));
    if (sat != Tristate.TRUE || aborted(handler)) {
        return null;
    }
    internalModel = solver.underlyingSolver().model();
    Assignment currentModel = solver.model(selectors);
    int currentBound = currentModel.positiveVariables().size();
    if (currentBound == 0) {
        solver.add(f.cc(CType.GE, 1, selectors));
        sat = solver.sat(satHandler(handler));
        if (aborted(handler)) {
            return null;
        } else if (sat == Tristate.FALSE) {
            return mkResultModel(solver, internalModel);
        } else {
            internalModel = solver.underlyingSolver().model();
            currentModel = solver.model(selectors);
            currentBound = currentModel.positiveVariables().size();
        }
    } else if (currentBound == selectors.size()) {
        return mkResultModel(solver, internalModel);
    }
    final Formula cc = f.cc(CType.GE, currentBound + 1, selectors);
    assert cc instanceof CardinalityConstraint;
    final CCIncrementalData incrementalData = solver.addIncrementalCC((CardinalityConstraint) cc);
    sat = solver.sat(satHandler(handler));
    if (aborted(handler)) {
        return null;
    }
    while (sat == Tristate.TRUE) {
        final LNGBooleanVector modelCopy = new LNGBooleanVector(solver.underlyingSolver().model());
        if (this.handler != null && !this.handler.foundBetterBound(() -> mkResultModel(solver, modelCopy))) {
            return null;
        }
        internalModel = modelCopy;
        currentModel = solver.model(selectors);
        currentBound = currentModel.positiveVariables().size();
        if (currentBound == selectors.size()) {
            return mkResultModel(solver, internalModel);
        }
        incrementalData.newLowerBoundForSolver(currentBound + 1);
        sat = solver.sat(satHandler(handler));
        if (aborted(handler)) {
            return null;
        }
    }
    return mkResultModel(solver, internalModel);
}