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

Example 46 with Variable

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

the class FinancePortfolioProblem method buildModel.

private static ExpressionsBasedModel buildModel(final BasicMatrix covariances, final BasicMatrix returns, final BigDecimal riskAversion) {
    ProgrammingError.throwIfNotSquare(covariances);
    ProgrammingError.throwIfNotEqualRowDimensions(covariances, returns);
    final int numberOfVariables = (int) returns.countRows();
    final Variable[] tmpVariables = new Variable[numberOfVariables];
    for (int i = 0; i < numberOfVariables; i++) {
        tmpVariables[i] = Variable.make("Asset_" + Integer.toString(i)).lower(ZERO).upper(ONE).weight(-returns.doubleValue(i));
    }
    final ExpressionsBasedModel retVal = new ExpressionsBasedModel(tmpVariables);
    final Expression tmp100P = retVal.addExpression("Balance");
    for (int i = 0; i < numberOfVariables; i++) {
        tmp100P.set(i, ONE);
    }
    tmp100P.level(ONE);
    final Expression tmpVar = retVal.addExpression("Variance");
    for (int i = 0; i < numberOfVariables; i++) {
        for (int j = 0; j < numberOfVariables; j++) {
            tmpVar.set(i, j, covariances.doubleValue(i, j));
        }
    }
    tmpVar.weight(BigFunction.DIVIDE.invoke(riskAversion, TWO));
    return retVal;
}

Example 47 with Variable

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

the class OJAlgoTest3 method main.

/**
 * @param args the command line arguments Objective: allocate the maximum qty, and try to keep
 *        proportionality between customer.
 */
public static void main(final String[] args) {
    /*
         * 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);
            });
        }
    });
    // - Maximise
    // model.options.validate = true;
    final Result result = model.maximise();
    BasicLogger.debug(result);
    // GOOD  OPTIMAL 560300.4702803734
    // WRONG OPTIMAL 560300.4015031556
    BasicLogger.debug("");
    BasicLogger.debug("");
    variables.forEach(v -> BasicLogger.debug(v.getName() + " = " + v.getValue().doubleValue()));
/*
         * WRONG ALLOCATION CUSTOMER_A_1|PRODUCT_2 = 236000.0 CUSTOMER_A_2|PRODUCT_2 = 0.0
         * CUSTOMER_A_3|PRODUCT_2 = 0.0 CUSTOMER_A_4|PRODUCT_2 = 0.0 CUSTOMER_A_5|PRODUCT_2 = 0.0
         * CUSTOMER_A_6|PRODUCT_2 = 0.0 CUSTOMER_A_7|PRODUCT_2 = 0.0 CUSTOMER_A_8|PRODUCT_2 = 0.0
         * CUSTOMER_A_9|PRODUCT_2 = 0.0 CUSTOMER_A_10|PRODUCT_2 = 0.0 CUSTOMER_A_11|PRODUCT_2 = 0.0
         * CUSTOMER_A_12|PRODUCT_2 = 0.0 CUSTOMER_A_13|PRODUCT_2 = 0.0 CUSTOMER_A_14|PRODUCT_2 = 0.0
         * CUSTOMER_B_1|PRODUCT_2 = 24000.0 CUSTOMER_B_1|PRODUCT_3 = 0.0 CUSTOMER_B_2|PRODUCT_2 = 12000.0
         * CUSTOMER_B_2|PRODUCT_3 = 0.0 CUSTOMER_B_3|PRODUCT_2 = 0.0 CUSTOMER_B_3|PRODUCT_3 = 300.0
         * CUSTOMER_C_1|PRODUCT_2 = 24000.0 CUSTOMER_C_1|PRODUCT_3 = 0.0 CUSTOMER_D_1|PRODUCT_4 = 20000.0
         * CUSTOMER_D_1|PRODUCT_5 = 0.0 CUSTOMER_D_1|PRODUCT_2 = 0.0 CUSTOMER_D_1|PRODUCT_3 = 0.0
         * CUSTOMER_E_1|PRODUCT_1 = 12000.0 CUSTOMER_F_1|PRODUCT_4 = 12000.0 CUSTOMER_F_1|PRODUCT_5 = 0.0
         * CUSTOMER_F_1|PRODUCT_2 = 0.0 CUSTOMER_F_1|PRODUCT_3 = 0.0 CUSTOMER_G_1|PRODUCT_4 = 72000.0
         * CUSTOMER_G_1|PRODUCT_5 = 0.0 CUSTOMER_G_1|PRODUCT_2 = 0.0 CUSTOMER_G_1|PRODUCT_3 = 0.0
         * CUSTOMER_H_1|PRODUCT_4 = 28000.0 CUSTOMER_H_1|PRODUCT_5 = 0.0 CUSTOMER_H_1|PRODUCT_2 = 0.0
         * CUSTOMER_H_1|PRODUCT_3 = 0.0 CUSTOMER_I_1|PRODUCT_4 = 24000.0 CUSTOMER_I_1|PRODUCT_5 = 0.0
         * CUSTOMER_I_1|PRODUCT_2 = 0.0 CUSTOMER_I_1|PRODUCT_3 = 0.0 CUSTOMER_J_1|PRODUCT_4 = 16000.0
         * CUSTOMER_J_1|PRODUCT_5 = 0.0 CUSTOMER_J_1|PRODUCT_2 = 0.0 CUSTOMER_J_1|PRODUCT_3 = 0.0
         * CUSTOMER_K_1|PRODUCT_4 = 24000.0 CUSTOMER_K_1|PRODUCT_5 = 0.0 CUSTOMER_K_1|PRODUCT_2 = 0.0
         * CUSTOMER_K_1|PRODUCT_3 = 0.0 CUSTOMER_L_1|PRODUCT_1 = 56000.0
         */
/*
         * GOOD ALLOCATION CUSTOMER_A_1|PRODUCT_2 = 80150.9434796 CUSTOMER_A_2|PRODUCT_2 = 48981.1320493
         * CUSTOMER_A_3|PRODUCT_2 = 13358.4905589 CUSTOMER_A_4|PRODUCT_2 = 40075.4716767
         * CUSTOMER_A_5|PRODUCT_2 = 0.0 CUSTOMER_A_6|PRODUCT_2 = 40075.4716767 CUSTOMER_A_7|PRODUCT_2 =
         * 13358.4905589 CUSTOMER_A_8|PRODUCT_2 = 0.0 CUSTOMER_A_9|PRODUCT_2 = 0.0 CUSTOMER_A_10|PRODUCT_2 =
         * 0.0 CUSTOMER_A_11|PRODUCT_2 = 0.0 CUSTOMER_A_12|PRODUCT_2 = 0.0 CUSTOMER_A_13|PRODUCT_2 = 0.0
         * CUSTOMER_A_14|PRODUCT_2 = 0.0 CUSTOMER_B_1|PRODUCT_2 = 24000.0 CUSTOMER_B_1|PRODUCT_3 = 0.0
         * CUSTOMER_B_2|PRODUCT_2 = 12000.0 CUSTOMER_B_2|PRODUCT_3 = 0.0 CUSTOMER_B_3|PRODUCT_2 = 0.0
         * CUSTOMER_B_3|PRODUCT_3 = 300.0 CUSTOMER_C_1|PRODUCT_2 = 24000.0 CUSTOMER_C_1|PRODUCT_3 = 0.0
         * CUSTOMER_D_1|PRODUCT_4 = 20000.0 CUSTOMER_D_1|PRODUCT_5 = 0.0 CUSTOMER_D_1|PRODUCT_2 = 0.0
         * CUSTOMER_D_1|PRODUCT_3 = 0.0 CUSTOMER_E_1|PRODUCT_1 = 12000.0 CUSTOMER_F_1|PRODUCT_4 = 12000.0
         * CUSTOMER_F_1|PRODUCT_5 = 0.0 CUSTOMER_F_1|PRODUCT_2 = 0.0 CUSTOMER_F_1|PRODUCT_3 = 0.0
         * CUSTOMER_G_1|PRODUCT_4 = 72000.0 CUSTOMER_G_1|PRODUCT_5 = 0.0 CUSTOMER_G_1|PRODUCT_2 = 0.0
         * CUSTOMER_G_1|PRODUCT_3 = 0.0 CUSTOMER_H_1|PRODUCT_4 = 28000.0 CUSTOMER_H_1|PRODUCT_5 = 0.0
         * CUSTOMER_H_1|PRODUCT_2 = 0.0 CUSTOMER_H_1|PRODUCT_3 = 0.0 CUSTOMER_I_1|PRODUCT_4 = 24000.0
         * CUSTOMER_I_1|PRODUCT_5 = 0.0 CUSTOMER_I_1|PRODUCT_2 = 0.0 CUSTOMER_I_1|PRODUCT_3 = 0.0
         * CUSTOMER_J_1|PRODUCT_4 = 16000.0 CUSTOMER_J_1|PRODUCT_5 = 0.0 CUSTOMER_J_1|PRODUCT_2 = 0.0
         * CUSTOMER_J_1|PRODUCT_3 = 0.0 CUSTOMER_K_1|PRODUCT_4 = 24000.0 CUSTOMER_K_1|PRODUCT_5 = 0.0
         * CUSTOMER_K_1|PRODUCT_2 = 0.0 CUSTOMER_K_1|PRODUCT_3 = 0.0 CUSTOMER_L_1|PRODUCT_1 = 56000.0
         */
}

Example 48 with Variable

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

the class P20150720 method buildModel2.

public static ExpressionsBasedModel buildModel2() {
    // List of Variable Names
    final List<String> variablesName = new ArrayList<>();
    variablesName.add("CUSTOMER_1|PRODUCT_TYPE_1");
    variablesName.add("CUSTOMER_2|PRODUCT_TYPE_1");
    variablesName.add("CUSTOMER_3|PRODUCT_TYPE_1");
    variablesName.add("CUSTOMER_3|PRODUCT_TYPE_2");
    variablesName.add("CUSTOMER_3|PRODUCT_TYPE_3");
    variablesName.add("CUSTOMER_3|PRODUCT_TYPE_4");
    variablesName.add("CUSTOMER_3|PRODUCT_TYPE_5");
    variablesName.add("CUSTOMER_4|PRODUCT_TYPE_1");
    variablesName.add("CUSTOMER_4|PRODUCT_TYPE_2");
    variablesName.add("CUSTOMER_5|PRODUCT_TYPE_2");
    variablesName.add("CUSTOMER_5|PRODUCT_TYPE_3");
    variablesName.add("CUSTOMER_5|PRODUCT_TYPE_4");
    variablesName.add("CUSTOMER_6|PRODUCT_TYPE_2");
    variablesName.add("CUSTOMER_6|PRODUCT_TYPE_3");
    variablesName.add("CUSTOMER_6|PRODUCT_TYPE_4");
    variablesName.add("CUSTOMER_6|PRODUCT_TYPE_5");
    /*
         * Constraints for each Customer = Demand of each Customer Sum of all variable linked to the customer
         * <= Demand.
         */
    final Map<String, Integer> constraintsCustomer = new LinkedHashMap<>();
    constraintsCustomer.put("CUSTOMER_1", 40_000);
    constraintsCustomer.put("CUSTOMER_2", 25_000);
    constraintsCustomer.put("CUSTOMER_3", 15_000);
    constraintsCustomer.put("CUSTOMER_4", 5_000);
    constraintsCustomer.put("CUSTOMER_5", 2_000);
    final double demandTotal = constraintsCustomer.values().stream().mapToDouble(e -> e.doubleValue()).sum();
    /*
         * Constraits for each product type = Stock per product type. Sum of all variable linked to this
         * product type <=
         */
    final Map<String, Integer> constraintsProduct = new HashMap<>();
    constraintsProduct.put("PRODUCT_TYPE_1", 50_000);
    constraintsProduct.put("PRODUCT_TYPE_2", 0);
    constraintsProduct.put("PRODUCT_TYPE_3", 0);
    constraintsProduct.put("PRODUCT_TYPE_4", 0);
    constraintsProduct.put("PRODUCT_TYPE_5", 0);
    final double stockTotal = constraintsProduct.values().stream().mapToDouble(e -> e.doubleValue()).sum();
    /*
         *
         */
    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);
        model.addVariable(var);
        variables.add(var);
    // BasicLogger.debug(var);
    });
    // BasicLogger.debug("---- Constraints customers ------");
    // Apply Customers constraints.
    constraintsCustomer.entrySet().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("---- 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) -
         * (SupplyTotal/DemandTotal) * DemandCustomerX )^2
         */
    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)) {
            linked.forEach(v1 -> {
                linked.forEach(v2 -> {
                    objective.set(v1, v2, -1);
                });
                objective.set(v1, ((2 * stockTotal) / demandTotal) * entry.getValue().doubleValue());
            });
        }
    });
    return model;
}

Example 49 with Variable

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

the class StrategyMixer method testStratCombQuadraticExpressionModel.

/**
 * This is test case using a reimplementation of the algorithm in {@link PortfolioMixer}.
 */
@Test
public void testStratCombQuadraticExpressionModel() {
    final BigDecimal[] tmpTarget = new BigDecimal[] { THIRD, THIRD, THIRD };
    final BigDecimal[] tmpStrat1 = new BigDecimal[] { HALF, HALF, ZERO };
    final BigDecimal[] tmpStrat2 = new BigDecimal[] { HALF, ZERO, HALF };
    final BigDecimal[] tmpStrat3 = new BigDecimal[] { ZERO, HALF, HALF };
    final BigDecimal[][] tmpStrats = new BigDecimal[][] { tmpStrat1, tmpStrat2, tmpStrat3 };
    final Variable[] tmpVars = new Variable[] { new Variable("S1"), new Variable("S2"), new Variable("S3"), Variable.makeBinary("B1"), Variable.makeBinary("B2"), Variable.makeBinary("B3") };
    for (int s = 0; s < 3; s++) {
        BigDecimal tmpVal = ZERO;
        for (int i = 0; i < 3; i++) {
            tmpVal = tmpVal.add(tmpTarget[i].multiply(tmpStrats[s][i]));
        }
        tmpVal = tmpVal.multiply(TWO).negate();
        tmpVars[s].weight(tmpVal);
        tmpVars[s].lower(ZERO);
        tmpVars[s].upper(ONE);
    }
    final ExpressionsBasedModel tmpModel = new ExpressionsBasedModel(tmpVars);
    // tmpModel.options.debug(IntegerSolver.class);
    // tmpModel.options.validate = false;
    final Expression tmpQuadObj = tmpModel.addExpression("Quadratic Objective Part");
    tmpQuadObj.weight(ONE);
    for (int row = 0; row < 3; row++) {
        for (int col = 0; col < 3; col++) {
            BigDecimal tmpVal = ZERO;
            for (int i = 0; i < 3; i++) {
                tmpVal = tmpVal.add(tmpStrats[row][i].multiply(tmpStrats[col][i]));
            }
            tmpQuadObj.set(row, col, tmpVal);
            tmpQuadObj.set(3 + row, 3 + col, tmpVal.multiply(THOUSANDTH));
        }
        final Expression tmpActive = tmpModel.addExpression(tmpVars[row].getName() + " Active");
        tmpActive.set(3 + row, ONE);
        tmpActive.set(row, NEG);
        tmpActive.lower(ZERO);
        if (OptimisationIntegerTests.DEBUG) {
            BasicLogger.debug(tmpActive.toString());
        }
    }
    final Expression tmpHundredPercent = tmpModel.addExpression("100%");
    tmpHundredPercent.level(ONE);
    tmpHundredPercent.set(0, ONE);
    tmpHundredPercent.set(1, ONE);
    tmpHundredPercent.set(2, ONE);
    if (OptimisationIntegerTests.DEBUG) {
        BasicLogger.debug(tmpHundredPercent.toString());
    }
    final Expression tmpStrategyCount = tmpModel.addExpression("Strategy Count");
    tmpStrategyCount.upper(TWO);
    tmpStrategyCount.set(3, ONE);
    tmpStrategyCount.set(4, ONE);
    tmpStrategyCount.set(5, ONE);
    if (OptimisationIntegerTests.DEBUG) {
        BasicLogger.debug(tmpStrategyCount.toString());
    }
    tmpModel.minimise();
    if (OptimisationIntegerTests.DEBUG) {
        BasicLogger.debug(tmpModel.toString());
        BasicLogger.debug(Arrays.toString(tmpVars));
    }
    int tmpUseCount = 0;
    double tmpTotalWeight = 0D;
    final Variable[] tmpSolution = new Variable[] { tmpVars[0], tmpVars[1], tmpVars[2] };
    for (final Variable tmpWeight : tmpSolution) {
        if (tmpWeight.getValue().signum() != 0) {
            tmpUseCount++;
            tmpTotalWeight += tmpWeight.getValue().doubleValue();
        }
    }
    TestUtils.assertEquals(TWO.intValue(), tmpUseCount);
    TestUtils.assertEquals(PrimitiveMath.ONE, tmpTotalWeight, 1E-14 / PrimitiveMath.THREE);
}

Example 50 with Variable

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

the class TestOjAlgo method testBug1.

public static void testBug1() {
    final Variable[] objective = new Variable[] { new Variable("X").weight(ONE), new Variable("Y").weight(ZERO), new Variable("Z").weight(ZERO) };
    objective[1].setInteger(true);
    final ExpressionsBasedModel model = new ExpressionsBasedModel(objective);
    // c1: X =0
    final Expression c1 = model.addExpression("c1");
    c1.level(ZERO);
    c1.set(0, ONE);
    // c2: -X +5Y =0
    final Expression c2 = model.addExpression("c2");
    c2.level(ZERO);
    c2.set(0, new BigDecimal(-1));
    c2.set(1, ONE);
    // c3: X -Z =0
    final Expression c3 = model.addExpression("c3");
    c3.level(ZERO);
    // bugs with this constraint
    c3.set(0, ONE);
    c3.set(2, new BigDecimal(-1));
    // but not with this one ???
    // c3.setLinearFactor(0, new BigDecimal(-1));
    // c3.setLinearFactor(2, ONE);
    final Optimisation.Result tmpResult = model.minimise();
    BasicLogger.debug(tmpResult.toString());
}