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  • 1
    Electronic Resource
    Electronic Resource
    Analyzing infeasible nonlinear programs (1995)
    Springer
    Computational optimization and applications 4 (1995), S. 167-179 
    Details
    ISSN: 1573-2894
    Keywords: infeasibility analysis ; nonlinear programming ; formulation assistance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Nonlinear optimizers often report infeasibility during the process of initial construction of a model, or alterations to an existing model. Because solvers are unable to decide feasibility of a nonlinear constraint set with perfect accuracy, there are numerous possible explanations: the physical model really is infeasible, there is an error in the nonlinear constraint set causing infeasibility, or the model is feasible but the initial point or solver parameters are poorly chosen. It is difficult to proceed to a diagnosis of the problem in a large NLP. This paper presents an algorithm providing automated assistance in analyzing infeasible NLPs. The deletion filtering algorithm isolates a Minimal Intractable Subsystem (MIS) of constraints, a minimal set of constraints which appears infeasible to the solver given a specified initial point and parameter settings. The MIS may be as small as a few constraints from among the very much larger set defining the original model, and helps to focus the examination, thereby speeding the diagnosis. A computer tool embodying the algorithm, LSGRG (MIS), is developed and applied to demonstration examples.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01302895
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    An effective polynomial-time heuristic for the minimum-cardinality IIS set-covering problem (1996)
    Springer
    Annals of mathematics and artificial intelligence 17 (1996), S. 127-144 
    Details
    ISSN: 1573-7470
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The state-of-the-art methods for analyzing infeasible linear programs concentrate on isolating Irreducible Infeasible Sets (IISs) of constraints. However, when there are numerous infeasibilities in the model, it is also useful to identify a minimum-cardinality set of constraints which, if removed from the LP, renders it feasible. This set of constraintscovers the IISs. This paper presents a heuristic algorithm for finding a small-cardinality set of constraints which covers the IISs in an infeasible LP. Empirical tests show that it finds a true minimum-cardinality cover over all of the examples in a test set, though this performance cannot be guaranteed in general.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02284627
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    Paper (German National Licenses)
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  • 3
    Book
    Book
    Feasibility and infeasibility in optimization /; 118 (2008)
    New York, NY :Springer,
    Details
    Title: Feasibility and infeasibility in optimization /; 118
    Author: Chinneck, John W.
    Publisher: New York, NY :Springer,
    Year of publication: 2008
    Pages: XXI, 270 S. : , graph. Darst.
    Series Statement: International series in operations research & management science 118
    ISBN: 0-387-74931-4 , 978-0-387-74931-0 , 978-0-387-74932-7
    Type of Medium: Book
    Language: English
    URL: http://www.zentralblatt-math.org/zmath/en/advanced/?q=an:1178.90369&format=complete
    URL: lizenzfrei
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