[jira] Updated: (MATH-286) SimplexSolver not working as expected?

["Benjamin McCann (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MATH-286?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Benjamin McCann updated MATH-286:
---------------------------------

    Attachment: SimplexTableau.patch
                SimplexSolverTest.patch
                SimplexSolver.patch

Happy Labor Day!  To celebrate, here's a new set of patches that adds the ability to deal with degeneracy in the SimplexTableau.
The test includes four tests: the two bugs in MATH-286, the bug from MATH-288, and the bug from MATH-290.  I think they should all go in to prevent a regression in the future.  They all run very quickly and there are a lot of edge cases in the Simplex algorithm, so I'd prefer to be safe.

> SimplexSolver not working as expected?
> --------------------------------------
>
>                 Key: MATH-286
>                 URL: https://issues.apache.org/jira/browse/MATH-286
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 2.0
>         Environment: Java 1.6.0_13 on  Windows XP 32-bit
>            Reporter: Andrea
>         Attachments: simplex.txt, SimplexSolver.patch, SimplexSolverTest.patch, SimplexSolverTest.patch, SimplexTableau.patch, SimplexTableau.patch
>
>
> I guess (but I could be wrong) that SimplexSolver does not always return the optimal solution, nor satisfies all the constraints...
> Consider this LP:
> max: 0.8 x0 + 0.2 x1 + 0.7 x2 + 0.3 x3 + 0.6 x4 + 0.4 x5;
> r1: x0 + x2 + x4 = 23.0;
> r2: x1 + x3 + x5 = 23.0;
> r3: x0 >= 10.0;
> r4: x2 >= 8.0;
> r5: x4 >= 5.0;
> LPSolve returns 25.8, with x0 = 10.0, x1 = 0.0, x2 = 8.0, x3 = 0.0, x4 = 5.0, x5 = 23.0;
> The same LP expressed in Apache commons math is:
> LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] { 0.8, 0.2, 0.7, 0.3, 0.6, 0.4 }, 0 );
> Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
> constraints.add(new LinearConstraint(new double[] { 1, 0, 1, 0, 1, 0 }, Relationship.EQ, 23.0));
> constraints.add(new LinearConstraint(new double[] { 0, 1, 0, 1, 0, 1 }, Relationship.EQ, 23.0));
> constraints.add(new LinearConstraint(new double[] { 1, 0, 0, 0, 0, 0 }, Relationship.GEQ, 10.0));
> constraints.add(new LinearConstraint(new double[] { 0, 0, 1, 0, 0, 0 }, Relationship.GEQ, 8.0));
> constraints.add(new LinearConstraint(new double[] { 0, 0, 0, 0, 1, 0 }, Relationship.GEQ, 5.0));
> RealPointValuePair solution = new SimplexSolver().optimize(f, constraints, GoalType.MAXIMIZE, true);
> that returns 22.20, with x0 = 15.0, x1 = 23.0, x2 = 8.0, x3 = 0.0, x4 = 0.0, x5 = 0.0;
> Is it possible SimplexSolver is buggy that way? The returned value is 22.20 instead of 25.8, and the last constraint (x4 >= 5.0) is not satisfied...
> Am I using the interface wrongly?

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