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Date: Thu, 24 Sep 2009 11:17:16 -0700 (PDT)
From: "Luc Maisonobe (JIRA)" <jira@apache.org>
To: issues@commons.apache.org
Subject: [jira] Commented: (MATH-299) SimplexSolver returns no feasible
 solution
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    [ https://issues.apache.org/jira/browse/MATH-299?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12759200#action_12759200 ] 

Luc Maisonobe commented on MATH-299:
------------------------------------

David, do you consider the version in the subversion repository fixes this bug ?
Can we change its state to resolved ?

> 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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