Examples with Expression org.ojalgo.optimisation.Expression used on opensource projects

Example 1 with Expression

use of org.ojalgo.optimisation.Expression in project cogcomp-nlp by CogComp.

the class OJalgoHook method addLessThanConstraint.

public void addLessThanConstraint(int[] i, double[] a, double b) {
    if (log) {
        System.out.print("OJalgoHook: addLessThanConstraint(");
        for (int idx = 0; idx < i.length; idx++) System.out.print("(i=" + i[idx] + ", a=" + a[idx] + ") ");
        System.out.println("b= " + b + ")");
    }
    numConstraints++;
    Expression constraint = model.addExpression("LessThanConstraint: " + Integer.toString(numConstraints));
    constraint.upper(b);
    for (int ind = 0; ind < i.length; ind++) {
        constraint.setLinearFactor(i[ind], a[ind]);
    // in jdk8:
    // constraint.set(i[ind], a[ind]);
    }
}

Example 2 with Expression

use of org.ojalgo.optimisation.Expression in project ojAlgo by optimatika.

the class ComPictetPamBamTest method setupModel.

/**
 * @param numberOfVars greater than 6
 */
void setupModel(final int numberOfVars) {
    if (numberOfVars < 6) {
        throw new IllegalArgumentException("numberOfVars must be >= 6 !!!");
    }
    // 
    // variables
    // 
    vars = new Variable[numberOfVars];
    vars[0] = new Variable("x0").lower(new BigDecimal(00.0)).upper(new BigDecimal(15.0));
    vars[1] = new Variable("x1").lower(new BigDecimal(17.0)).upper(new BigDecimal(27.0));
    vars[2] = new Variable("x2").lower(new BigDecimal(19.0)).upper(new BigDecimal(34.0));
    vars[3] = new Variable("x3").lower(new BigDecimal(25.0)).upper(new BigDecimal(48.0));
    vars[4] = new Variable("x4").lower(new BigDecimal(05.0)).upper(new BigDecimal(18.0));
    vars[5] = new Variable("x5").lower(new BigDecimal(02.0)).upper(new BigDecimal(09.0));
    for (int i = 6; i < numberOfVars; ++i) {
        vars[i] = new Variable("x" + i).level(BigMath.ZERO);
    }
    // 
    // minimise distance to this point
    // 
    point = new BigDecimal[numberOfVars];
    point[0] = new BigDecimal(1.0);
    point[1] = new BigDecimal(25.0);
    point[2] = new BigDecimal(33.0);
    point[3] = new BigDecimal(29.0);
    point[4] = new BigDecimal(9.0);
    point[5] = new BigDecimal(2.0);
    for (int i = 6; i < numberOfVars; ++i) {
        point[i] = new BigDecimal(0.0);
    }
    // 
    // model
    // 
    model = new ExpressionsBasedModel(vars);
    // 
    // objective function
    // 
    {
        final int tmpLength = model.countVariables();
        final Expression retVal = model.addExpression("objective");
        for (int ij = 0; ij < tmpLength; ij++) {
            retVal.set(ij, ij, ONE);
        }
        final BigDecimal tmpLinearWeight = TWO.negate();
        for (int i = 0; i < tmpLength; i++) {
            retVal.set(i, Arrays.asList(point).get(i).multiply(tmpLinearWeight));
        }
        final Expression e = retVal;
        e.weight(BigMath.HALF);
    }
    // 
    // sum(xi) = 100.0
    // 
    {
        final int tmpLength = model.countVariables();
        final Expression retVal = model.addExpression("sum(xi) = 100.0");
        for (int i = 0; i < tmpLength; i++) {
            retVal.set(i, ONE);
        }
        final Expression e = retVal;
        e.level(BigMath.HUNDRED);
    }
    // 
    // x1 + x2 <= 45
    // 
    {
        final Expression e = model.addExpression("x1 + x2 <= 45.0");
        e.set(1, BigMath.ONE);
        e.set(2, BigMath.ONE);
        e.lower(BigMath.ZERO).upper(new BigDecimal(45.0));
    }
    // 
    // x4 - 2*x5 = 0
    // 
    {
        final Expression e = model.addExpression("x4 - 2*x5 = 0");
        e.set(4, BigMath.ONE);
        e.set(5, BigMath.TWO.negate());
        e.level(BigMath.ZERO);
    }
// model.options.debug(ConvexSolver.class);
}

Example 3 with Expression

use of org.ojalgo.optimisation.Expression in project ojAlgo by optimatika.

the class ConvexProblems method doEarly2008.

static void doEarly2008(final Variable[] variables, final Access2D<?> covariances, final Access1D<?> expected) {
    final ExpressionsBasedModel tmpModel = new ExpressionsBasedModel(variables);
    final Expression tmpVariance = tmpModel.addExpression("Variance");
    tmpVariance.setQuadraticFactors(tmpModel.getVariables(), covariances);
    tmpVariance.weight(BigMath.PI.multiply(BigMath.E).multiply(BigMath.HALF));
    final Expression tmpBalance = tmpModel.addExpression("Balance");
    tmpBalance.setLinearFactorsSimple(tmpModel.getVariables());
    tmpBalance.level(BigMath.ONE);
    // tmpModel.options.debug(ConvexSolver.class);
    // tmpModel.options.validate = false;
    final Result tmpActualResult = tmpModel.minimise();
    final NumberContext tmpAccuracy = StandardType.PERCENT.newPrecision(5);
    TestUtils.assertTrue(tmpModel.validate(Array1D.BIG.copy(expected), tmpAccuracy));
    TestUtils.assertTrue(tmpModel.validate(tmpActualResult, tmpAccuracy));
    final TwiceDifferentiable<Double> tmpObjective = tmpModel.objective().toFunction();
    final double tmpExpObjFuncVal = tmpObjective.invoke(Access1D.asPrimitive1D(expected));
    final double tmpActObjFuncVal = tmpObjective.invoke(Access1D.asPrimitive1D(tmpActualResult));
    TestUtils.assertEquals(tmpExpObjFuncVal, tmpActObjFuncVal, tmpAccuracy);
    TestUtils.assertEquals(expected, tmpActualResult, tmpAccuracy);
    // Test that the LinearSolver can determine feasibility
    final ExpressionsBasedModel relaxedModel = tmpModel.relax(false);
    final Optimisation.Result tmpLinearResult = relaxedModel.minimise();
    TestUtils.assertStateNotLessThanFeasible(tmpLinearResult);
    OptimisationConvexTests.assertDirectAndIterativeEquals(tmpModel, tmpAccuracy);
}

Example 4 with Expression

use of org.ojalgo.optimisation.Expression in project ojAlgo by optimatika.

the class ConvexProblems method testP20111129.

/**
 * ojAlgo could not solve this, but LOQO (and others) could. I re-implemented the problem code just to
 * verify there was no problem there. http://bugzilla.optimatika.se/show_bug.cgi?id=11
 */
@Test
public void testP20111129() {
    final Variable x1 = new Variable("X1");
    final Variable x2 = new Variable("X2").lower(BigMath.HUNDRED.negate()).upper(BigMath.HUNDRED);
    final Variable x3 = new Variable("X3").lower(BigMath.ZERO);
    final Variable x4 = new Variable("X4").lower(BigMath.ZERO);
    final Variable[] tmpVariables = new Variable[] { x1, x2, x3, x4 };
    final ExpressionsBasedModel tmpModel = new ExpressionsBasedModel(tmpVariables);
    final Expression tmpObjExpr = tmpModel.addExpression("Objective");
    tmpModel.setMinimisation();
    tmpObjExpr.set(2, 2, BigMath.HALF);
    tmpObjExpr.set(3, 3, BigMath.TWO);
    tmpObjExpr.set(2, 3, BigMath.TWO.negate());
    tmpObjExpr.set(0, BigMath.THREE);
    tmpObjExpr.set(1, BigMath.TWO.negate());
    tmpObjExpr.set(2, BigMath.ONE);
    tmpObjExpr.set(3, BigMath.FOUR.negate());
    tmpObjExpr.weight(BigMath.ONE);
    Expression tmpConstrExpr;
    tmpConstrExpr = tmpModel.addExpression("C1").lower(BigMath.FOUR);
    tmpConstrExpr.set(0, BigMath.ONE);
    tmpConstrExpr.set(1, BigMath.ONE);
    tmpConstrExpr.set(2, BigMath.FOUR.negate());
    tmpConstrExpr.set(3, BigMath.TWO);
    tmpConstrExpr = tmpModel.addExpression("C2").upper(BigMath.SIX);
    tmpConstrExpr.set(0, BigMath.THREE.negate());
    tmpConstrExpr.set(1, BigMath.ONE);
    tmpConstrExpr.set(2, BigMath.TWO.negate());
    tmpConstrExpr = tmpModel.addExpression("C3").level(BigMath.NEG);
    tmpConstrExpr.set(1, BigMath.ONE);
    tmpConstrExpr.set(3, BigMath.NEG);
    tmpConstrExpr = tmpModel.addExpression("C4").level(BigMath.ZERO);
    tmpConstrExpr.set(0, BigMath.ONE);
    tmpConstrExpr.set(1, BigMath.ONE);
    tmpConstrExpr.set(2, BigMath.NEG);
    // tmpModel.options.debug(ConvexSolver.class);
    final Result tmpResult = tmpModel.minimise();
    final double tmpObjFuncVal = tmpResult.getValue();
    TestUtils.assertEquals(-5.281249989, tmpObjFuncVal, new NumberContext(7, 6));
    final double[] tmpExpected = new double[] { -1.1875, 1.5625, 0.375, 2.5625 };
    for (int i = 0; i < tmpExpected.length; i++) {
        TestUtils.assertEquals(tmpExpected[i], tmpVariables[i].getValue().doubleValue(), new NumberContext(5, 4));
    }
    OptimisationConvexTests.assertDirectAndIterativeEquals(tmpModel, null);
}

Example 5 with Expression

use of org.ojalgo.optimisation.Expression in project ojAlgo by optimatika.

the class P20150720 method buildModel3.

/**
 * Sent in 2015-09-03
 */
public static ExpressionsBasedModel buildModel3() {
    /*
         * 5 Products with associated Qty.
         */
    final Map<String, Integer> constraintsProduct = new HashMap<>();
    constraintsProduct.put("PRODUCT_1", 296_000);
    constraintsProduct.put("PRODUCT_2", 888_000);
    constraintsProduct.put("PRODUCT_3", 636_000);
    constraintsProduct.put("PRODUCT_4", 220_000);
    constraintsProduct.put("PRODUCT_5", 0);
    final double stockTotal = constraintsProduct.values().stream().mapToDouble(e -> e.doubleValue()).sum();
    // BasicLogger.debug("STOCK_TOTAL " + stockTotal);
    /*
         * Demand of each Customers
         */
    final Map<String, Integer> constraintsCustomer = new LinkedHashMap<>();
    constraintsCustomer.put("CUSTOMER_A_1", 72_000);
    constraintsCustomer.put("CUSTOMER_A_2", 44_000);
    constraintsCustomer.put("CUSTOMER_A_3", 12_000);
    constraintsCustomer.put("CUSTOMER_A_4", 36_000);
    constraintsCustomer.put("CUSTOMER_A_5", 0);
    constraintsCustomer.put("CUSTOMER_A_6", 36_000);
    constraintsCustomer.put("CUSTOMER_A_7", 12_000);
    constraintsCustomer.put("CUSTOMER_A_8", 0);
    constraintsCustomer.put("CUSTOMER_A_9", 0);
    constraintsCustomer.put("CUSTOMER_A_10", 12_000);
    constraintsCustomer.put("CUSTOMER_A_11", 12_000);
    constraintsCustomer.put("CUSTOMER_A_12", 0);
    constraintsCustomer.put("CUSTOMER_A_13", 0);
    constraintsCustomer.put("CUSTOMER_A_14", 0);
    constraintsCustomer.put("CUSTOMER_B_1", 24_000);
    constraintsCustomer.put("CUSTOMER_B_2", 12_000);
    constraintsCustomer.put("CUSTOMER_B_3", 300);
    constraintsCustomer.put("CUSTOMER_C_1", 24_000);
    constraintsCustomer.put("CUSTOMER_D_1", 20_000);
    constraintsCustomer.put("CUSTOMER_E_1", 12_000);
    constraintsCustomer.put("CUSTOMER_F_1", 12_000);
    constraintsCustomer.put("CUSTOMER_G_1", 72_000);
    constraintsCustomer.put("CUSTOMER_H_1", 28_000);
    constraintsCustomer.put("CUSTOMER_I_1", 24_000);
    constraintsCustomer.put("CUSTOMER_J_1", 16_000);
    constraintsCustomer.put("CUSTOMER_K_1", 24_000);
    constraintsCustomer.put("CUSTOMER_L_1", 56_000);
    final double demandTotal = constraintsCustomer.values().stream().mapToDouble(e -> e.doubleValue()).sum();
    // BasicLogger.debug("DEMAND_TOTAL " + demandTotal);
    /*
         * User constraint. In this case, user want to allocate 236_000 Qty on Customer_A_*
         */
    final double userConstraintQty = 236_000;
    final List<String> userConstraint = new ArrayList<>();
    userConstraint.add("CUSTOMER_A_1|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_2|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_3|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_4|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_5|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_6|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_7|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_8|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_9|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_10|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_11|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_12|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_13|PRODUCT_2");
    userConstraint.add("CUSTOMER_A_14|PRODUCT_2");
    // List of Variable Names
    final List<String> variablesName = new ArrayList<>();
    variablesName.add("CUSTOMER_A_1|PRODUCT_2");
    variablesName.add("CUSTOMER_A_2|PRODUCT_2");
    variablesName.add("CUSTOMER_A_3|PRODUCT_2");
    variablesName.add("CUSTOMER_A_4|PRODUCT_2");
    variablesName.add("CUSTOMER_A_5|PRODUCT_2");
    variablesName.add("CUSTOMER_A_6|PRODUCT_2");
    variablesName.add("CUSTOMER_A_7|PRODUCT_2");
    variablesName.add("CUSTOMER_A_8|PRODUCT_2");
    variablesName.add("CUSTOMER_A_9|PRODUCT_2");
    variablesName.add("CUSTOMER_A_10|PRODUCT_2");
    variablesName.add("CUSTOMER_A_11|PRODUCT_2");
    variablesName.add("CUSTOMER_A_12|PRODUCT_2");
    variablesName.add("CUSTOMER_A_13|PRODUCT_2");
    variablesName.add("CUSTOMER_A_14|PRODUCT_2");
    variablesName.add("CUSTOMER_B_1|PRODUCT_2");
    variablesName.add("CUSTOMER_B_1|PRODUCT_3");
    variablesName.add("CUSTOMER_B_2|PRODUCT_2");
    variablesName.add("CUSTOMER_B_2|PRODUCT_3");
    variablesName.add("CUSTOMER_B_3|PRODUCT_2");
    variablesName.add("CUSTOMER_B_3|PRODUCT_3");
    variablesName.add("CUSTOMER_C_1|PRODUCT_2");
    variablesName.add("CUSTOMER_C_1|PRODUCT_3");
    variablesName.add("CUSTOMER_D_1|PRODUCT_4");
    variablesName.add("CUSTOMER_D_1|PRODUCT_5");
    variablesName.add("CUSTOMER_D_1|PRODUCT_2");
    variablesName.add("CUSTOMER_D_1|PRODUCT_3");
    variablesName.add("CUSTOMER_E_1|PRODUCT_1");
    variablesName.add("CUSTOMER_F_1|PRODUCT_4");
    variablesName.add("CUSTOMER_F_1|PRODUCT_5");
    variablesName.add("CUSTOMER_F_1|PRODUCT_2");
    variablesName.add("CUSTOMER_F_1|PRODUCT_3");
    variablesName.add("CUSTOMER_G_1|PRODUCT_4");
    variablesName.add("CUSTOMER_G_1|PRODUCT_5");
    variablesName.add("CUSTOMER_G_1|PRODUCT_2");
    variablesName.add("CUSTOMER_G_1|PRODUCT_3");
    variablesName.add("CUSTOMER_H_1|PRODUCT_4");
    variablesName.add("CUSTOMER_H_1|PRODUCT_5");
    variablesName.add("CUSTOMER_H_1|PRODUCT_2");
    variablesName.add("CUSTOMER_H_1|PRODUCT_3");
    variablesName.add("CUSTOMER_I_1|PRODUCT_4");
    variablesName.add("CUSTOMER_I_1|PRODUCT_5");
    variablesName.add("CUSTOMER_I_1|PRODUCT_2");
    variablesName.add("CUSTOMER_I_1|PRODUCT_3");
    variablesName.add("CUSTOMER_J_1|PRODUCT_4");
    variablesName.add("CUSTOMER_J_1|PRODUCT_5");
    variablesName.add("CUSTOMER_J_1|PRODUCT_2");
    variablesName.add("CUSTOMER_J_1|PRODUCT_3");
    variablesName.add("CUSTOMER_K_1|PRODUCT_4");
    variablesName.add("CUSTOMER_K_1|PRODUCT_5");
    variablesName.add("CUSTOMER_K_1|PRODUCT_2");
    variablesName.add("CUSTOMER_K_1|PRODUCT_3");
    variablesName.add("CUSTOMER_L_1|PRODUCT_1");
    /*
         *
         */
    final ExpressionsBasedModel model = new ExpressionsBasedModel();
    final List<Variable> variables = new ArrayList<>();
    /*
         * Create All Variables:
         */
    // BasicLogger.debug("---- Variable creation ------");
    variablesName.forEach(name -> {
        final Variable var = Variable.make(name).lower(0.0).weight(1.0);
        model.addVariable(var);
        variables.add(var);
    // BasicLogger.debug(var);
    });
    // BasicLogger.debug("---- Constraints customers ------");
    // Apply Customers constraints.
    // CUSTOMER_A of Demand constraint because managed by user constraints.
    constraintsCustomer.entrySet().stream().filter(e -> !e.getKey().startsWith("CUSTOMER_A")).forEach(entry -> {
        final List<Variable> linked = variables.stream().filter(v -> v.getName().startsWith(entry.getKey())).collect(Collectors.toList());
        final Expression constraint = model.addExpression("CONSTRAINTS_" + entry.getKey());
        constraint.upper(entry.getValue().doubleValue());
        constraint.setLinearFactorsSimple(linked);
    // BasicLogger.debug(constraint);
    });
    // BasicLogger.debug("---- User Constraints Customers ------");
    // Apply Product Type constraints.
    final List<Variable> userLinked = variables.stream().filter(v -> userConstraint.contains(v.getName())).collect(Collectors.toList());
    final Expression constraintUser = model.addExpression("CONSTRAINTS_USER_CUSTOMER_A");
    constraintUser.level(userConstraintQty);
    constraintUser.setLinearFactorsSimple(userLinked);
    // BasicLogger.debug(constraintUser);
    // BasicLogger.debug("---- Constraints Product ------");
    // Apply Product Type constraints.
    constraintsProduct.entrySet().forEach(entry -> {
        final List<Variable> linked = variables.stream().filter(v -> v.getName().endsWith(entry.getKey())).collect(Collectors.toList());
        final Expression constraint = model.addExpression("CONSTRAINTS_" + entry.getKey());
        constraint.upper(entry.getValue().doubleValue());
        constraint.setLinearFactorsSimple(linked);
    // BasicLogger.debug(constraint);
    });
    /*
         * Objective expression. - Maximize the Sum of all variables - Minimize the Sum of square error vs
         * proportionality.
         */
    // BasicLogger.debug("---- Objective  ------");
    final Expression objective = model.addExpression("OBJECTIVE").weight(-1.0);
    // - Maximize the Sum of all variables
    // objective.setLinearFactorsSimple(variables);
    // BasicLogger.debug("---- Error formula ------");
    /*
         * Example: x1, x2, x3 linked variables for Customer X Error = ( (x1+x2+x3) / Target - 1 )^2 * ratio
         */
    constraintsCustomer.entrySet().forEach(entry -> {
        final List<Variable> linked = variables.stream().filter(v -> v.getName().startsWith(entry.getKey())).collect(Collectors.toList());
        if (!linked.isEmpty() && (entry.getValue().doubleValue() > 0)) {
            final double demand = entry.getValue();
            final double ratio = demand / demandTotal;
            final double target = stockTotal * ratio;
            linked.forEach(v1 -> {
                linked.forEach(v2 -> {
                    objective.set(v1, v2, ratio / (target * target));
                });
                objective.set(v1, (-2.0 * ratio) / target);
            });
        }
    });
    return model;
}