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oj! Algorithms - ojAlgo - is Open Source Java code that has to do with mathematics, linear algebra and optimisation.
/*
* Copyright 1997-2020 Optimatika
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
package org.ojalgo.optimisation.linear;
import static org.ojalgo.function.constant.PrimitiveMath.*;
import org.ojalgo.matrix.store.MatrixStore;
import org.ojalgo.matrix.store.RowsSupplier;
import org.ojalgo.optimisation.Optimisation;
import org.ojalgo.optimisation.convex.ConvexSolver;
import org.ojalgo.structure.Access1D;
import org.ojalgo.structure.ElementView1D;
import org.ojalgo.structure.Mutate1D;
import org.ojalgo.structure.Mutate2D;
import org.ojalgo.structure.RowView;
import org.ojalgo.type.context.NumberContext;
final class DualSimplex extends SimplexSolver {
public static Optimisation.Result solve(final ConvexSolver.Builder convex, final Optimisation.Options options) {
SimplexTableau tableau = DualSimplex.build(convex, options);
DualSimplex solver = new DualSimplex(tableau, options);
Result result = solver.solve();
Optimisation.Result retVal = DualSimplex.toConvexState(result, convex);
return retVal;
}
static SimplexTableau build(final ConvexSolver.Builder convex, final Optimisation.Options options) {
int numbVars = convex.countVariables();
int numbEqus = convex.countEqualityConstraints();
int numbInes = convex.countInequalityConstraints();
SimplexTableau retVal = SimplexTableau.make(numbVars, numbEqus + numbEqus + numbInes, 0, options);
Mutate1D obj = retVal.objective();
Mutate2D constrBody = retVal.constraintsBody();
Mutate1D constrRHS = retVal.constraintsRHS();
MatrixStore convexC = convex.getC();
MatrixStore convexAE = convex.getAE();
MatrixStore convexBE = convex.getBE();
RowsSupplier convexAI = convex.getAI();
MatrixStore convexBI = convex.getBI();
for (int i = 0; i < numbVars; i++) {
double rhs = convexC.doubleValue(i);
boolean neg = retVal.negative[i] = NumberContext.compare(rhs, ZERO) < 0;
for (int j = 0; j < numbEqus; j++) {
double valE = convexAE.doubleValue(j, i);
constrBody.set(i, j, neg ? -valE : valE);
constrBody.set(i, numbEqus + j, neg ? valE : -valE);
}
constrRHS.set(i, neg ? -rhs : rhs);
}
for (RowView rowV : convexAI.rows()) {
long tabJ = rowV.row();
for (ElementView1D elemV : rowV.nonzeros()) {
int tabI = Math.toIntExact(elemV.index());
double tabVal = elemV.doubleValue();
constrBody.set(tabI, numbEqus + numbEqus + tabJ, retVal.negative[tabI] ? -tabVal : tabVal);
}
}
for (int j = 0; j < numbEqus; j++) {
obj.set(j, convexBE.doubleValue(j));
obj.set(numbEqus + j, -convexBE.doubleValue(j));
}
for (int j = 0; j < numbInes; j++) {
obj.set(numbEqus + numbEqus + j, convexBI.doubleValue(j));
}
// BasicLogger.debug("Dual", retVal);
// BasicLogger.debug("Negs (dual): {}", Arrays.toString(retVal.negative));
return retVal;
}
static Optimisation.Result toConvexState(final Result result, final ConvexSolver.Builder convex) {
int numbEqus = convex.countEqualityConstraints();
int numbInes = convex.countInequalityConstraints();
Access1D multipliers = result.getMultipliers().get();
Optimisation.Result retVal = new Optimisation.Result(result.getState(), result.getValue(), result);
retVal.multipliers(new Access1D() {
public long count() {
return numbEqus + numbInes;
}
public double doubleValue(final long index) {
if (index < numbEqus) {
return -(multipliers.doubleValue(index) - multipliers.doubleValue(numbEqus + index));
} else {
return -multipliers.doubleValue(numbEqus + index);
}
}
public Double get(final long index) {
return this.doubleValue(index);
}
@Override
public String toString() {
return Access1D.toString(this);
}
});
return retVal;
}
DualSimplex(final SimplexTableau tableau, final Options solverOptions) {
super(tableau, solverOptions);
}
@Override
protected Access1D extractMultipliers() {
return super.extractSolution();
}
@Override
protected Access1D extractSolution() {
return super.extractMultipliers();
}
@Override
protected State getState() {
State state = super.getState();
if (state == State.UNBOUNDED) {
return State.INFEASIBLE;
} else if (!state.isFeasible()) {
return State.UNBOUNDED;
} else {
return state;
}
}
}