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Date: Sun, 22 Jul 2012 01:49:34 +0000 (UTC)
From: "Gilles (JIRA)" <jira@apache.org>
To: issues@commons.apache.org
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Subject: [jira] [Updated] (MATH-828) Not expected UnboundedSolutionException
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     [ https://issues.apache.org/jira/browse/MATH-828?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Gilles updated MATH-828:
------------------------

    Fix Version/s:     (was: 3.0)
                   3.1
    
> Not expected UnboundedSolutionException
> ---------------------------------------
>
>                 Key: MATH-828
>                 URL: https://issues.apache.org/jira/browse/MATH-828
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 3.0
>         Environment: Intel Core i5-2300 Windows XP SP3
>            Reporter: Alexey Slepov
>              Labels: linear, math, programming
>             Fix For: 3.1
>
>         Attachments: ApacheSimplexWrapper.java, ApacheSimplexWrapperTest.java, Entity.java, commons-math3-3.0.jar
>
>
> SimplexSolver throws UnboundedSolutionException when trying to solve minimization linear programming problem. The number of exception thrown depends on the number of variables.
> In order to see that behavior of SimplexSolver first try to run JUnit test setting a final variable ENTITIES_COUNT = 2 and that will give almost good result and then set it to 15 and you'll get a massive of unbounded exceptions.
> First iteration is runned with predefined set of input data with which the Solver gives back an appropriate result.
> The problem itself is well tested by it's authors (mathematicians who I believe know what they developed) using Matlab 10 with no unbounded solutions on the same rules of creatnig random variables values.
> What is strange to me is the dependence of the number of UnboundedSolutionException exceptions on the number of variables in the problem.
> The problem is formulated as
> min(1*t + 0*L) (for every r-th subject)
> s.t.
> -q(r) + QL >= 0
> x(r)t - XL >= 0
> L >= 0
> where 
> r = 1..R, 
> L = {l(1), l(2), ..., l(R)} (vector of R rows and 1 column),
> Q - coefficients matrix MxR
> X - coefficients matrix NxR 

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