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From "David (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MATH-299) SimplexSolver returns no feasible solution
Date Thu, 24 Sep 2009 19:03:16 GMT
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[ https://issues.apache.org/jira/browse/MATH-299?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12759214#action_12759214
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David commented on MATH-299:
----------------------------

I changed to the subversion repository and it seems fixed.

> 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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