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https://issues.apache.org/jira/browse/MATH-299?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12758444#action_12758444
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Benjamin McCann commented on MATH-299:
--------------------------------------
We might be better than lp_solve on this one! This worked fine for me and gave
me the same answer as Lindo (1.398257)
David, did you use Commons Math 2.0? The seemed to work fine for me when I
used Commons Math compiled from the Subversion repository. I'd recommend using
the Subversion version because we've fixed numerous bugs that were present in
the 2.0 release.
@Test
public void testMath299() throws OptimizationException {
LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] {
1, 0, 0, 0, 0}, 0 );
Collection<LinearConstraint> constraints = new
ArrayList<LinearConstraint> ();
constraints.add(new LinearConstraint(new double[] { -1,
1.7316145027890766, 1.3584341412980305, 0.9305633063383639, 1.687117394945513
}, Relationship.GEQ, 0));
constraints.add(new LinearConstraint(new double[] { -1,
0.6617060079461883, 1.4862459822191323, 0.7692647272328988, 0.7329140944025636
}, Relationship.GEQ, 0));
constraints.add(new LinearConstraint(new double[] { -1,
1.3255966888982322, 286.21607948837584, 1.135907611434458, 0.9803367440299271
}, Relationship.GEQ, 0));
constraints.add(new LinearConstraint(new double[] { -1,
0.5428682596573682, 1.5745685116536952, 1.4834419186882808, 1.2884923232048968
}, Relationship.GEQ, 0));
constraints.add(new LinearConstraint(new double[] {0, 1, 1, 1, 1},
Relationship.EQ, 1));
RealPointValuePair solution = new SimplexSolver().optimize(f,
constraints, GoalType.MAXIMIZE, true);
Assert.assertEquals(1.398257, solution.getValue(), .0001);
}
> SimplexSolver returns no feasible solution
> ------------------------------------------
>
> Key: MATH-299
> URL: https://issues.apache.org/jira/browse/MATH-299
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 2.0
> Environment: Windows XP commons Math 2.0 jre 1.6.0.16
> Reporter: David
> Original Estimate: 8h
> Remaining Estimate: 8h
>
> I am trying to optimize this:
> maximize: v
> v <= a1*p1 + a2*p2 + a3*p3 + a4*p4
> v <= b1*p1 + b2*p2 + b3*p3 + b4*p4
> v <= c1*p1 + c2*p2 + c3*p3 + c4*p4
> v <= d1*p1 + d2*p2 + d3*p3 + d4*p4
> p1 + p2 + p3 + p4 = 1
> where a1-d4 are constant specified below by the code (i didn't want to copy
> and paste them up here. you can look below to see what they are in the
> objective function).
> LinearObjectiveFunction f = new LinearObjectiveFunction(
>
> new double[] { 1,
> 0,
> 0, 0, 0}, 0 );
> Collection<LinearConstraint> constraints = new
> ArrayList<LinearConstraint> ();
> constraints.add(new LinearConstraint(new double[] { -1,
> 1.7316145027890766,
> 1.3584341412980305,
> 0.9305633063383639,
> 1.687117394945513
> },
> Relationship.GEQ, 0));
> constraints.add(new LinearConstraint(new double[] { -1,
> 0.6617060079461883,
> 1.4862459822191323,
> 0.7692647272328988,
> 0.7329140944025636
> },
> Relationship.GEQ, 0));
> constraints.add(new LinearConstraint(new double[] { -1,
> 1.3255966888982322,
> 286.21607948837584,
> 1.135907611434458,
> 0.9803367440299271
> },
> Relationship.GEQ, 0));
> constraints.add(new LinearConstraint(new double[] { -1,
> 0.5428682596573682,
> 1.5745685116536952,
> 1.4834419186882808,
> 1.2884923232048968
> },
> Relationship.GEQ, 0));
> constraints.add(new LinearConstraint(new double[] {0, 1, 1, 1,
> 1},
> Relationship.EQ, 1));
> RealPointValuePair solution = null;
> try {
>
> solution = new SimplexSolver().optimize(f, constraints,
> GoalType.MAXIMIZE, true);
> }
> catch (OptimizationException e) {
> e.printStackTrace();
> }
> I get this error back from the SimplexSolver.
> org.apache.commons.math.optimization.linear.NoFeasibleSolutionException: no
> feasible solution
> at
> org.apache.commons.math.optimization.linear.SimplexSolver.solvePhase1(SimplexSolver.java:177)
> at
> org.apache.commons.math.optimization.linear.SimplexSolver.doOptimize(SimplexSolver.java:187)
> at
> org.apache.commons.math.optimization.linear.AbstractLinearOptimizer.optimize(AbstractLinearOptimizer.java:106)
> at Runner.main(Runner.java:101)
> One interesting thing to note is that if you round all the numbers to the
> nearest 100's place, it works. If you keep it with the floating point
> precision shown here, it doesn't.
>
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