Milan Hladík's Publications:

Interval convex quadratic programming problems in a general form

Milan Hladík. Interval convex quadratic programming problems in a general form. Cent. Eur. J. Oper. Res., 25(3):725–737, 2017.

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Abstract

This paper addresses the problem of computing the minimal and the maximal optimal value of a convex quadratic programming (CQP) problem when the coefficients are subject to perturbations in given intervals. Contrary to the previous results concerning on some special forms of CQP only, we present a unified method to deal with interval CQP problems. The problem can be formulated by using equation, inequalities or both, and by using sign-restricted variables or sign-unrestricted variables or both. We propose simple formulas for calculating the minimal and maximal optimal values. Due to NP-hardness of the problem, the formulas are exponential with respect to some characteristics. On the other hand, there are large sub-classes of problems that are polynomially solvable. For the general intractable case we propose an approximation algorithm. We illustrate our approach by a geometric problem of determining the distance of uncertain polytopes. Eventually, we extend our results to quadratically constrained CQP, and state some open problems.

Errata

The equation in Theorem 2 is correct, but the proof must be conducted another way. In Theorem 4, a constraint qualification is missing, and the proof also needs more thorough derivation.

BibTeX

@article{Hla2017c,
 author = "Milan Hlad\'{\i}k",
 title = "Interval convex quadratic programming problems in a general form",
 journal = "Cent. Eur. J. Oper. Res.",
 fjournal = "Central European Journal of Operations Research",
 volume = "25",
 number = "3",
 pages = "725-737",
 year = "2017",
 doi = "10.1007/s10100-016-0445-8",
 issn = "1613-9178",
 bib2html_dl_html = "https://doi.org/10.1007/s10100-016-0445-8",
 bib2html_dl_pdf = "http://rdcu.be/nhN2",
 abstract = "This paper addresses the problem of computing the minimal and the maximal optimal value of a convex quadratic programming (CQP) problem when the coefficients are subject to perturbations in given intervals. Contrary to the previous results concerning on some special forms of CQP only, we present a unified method to deal with interval CQP problems. The problem can be formulated by using equation, inequalities or both, and by using sign-restricted variables or sign-unrestricted variables or both. We propose simple formulas for calculating the minimal and maximal optimal values. Due to NP-hardness of the problem, the formulas are exponential with respect to some characteristics. On the other hand, there are large sub-classes of problems that are polynomially solvable. For the general intractable case we propose an approximation algorithm. We illustrate our approach by a geometric problem of determining the distance of uncertain polytopes. Eventually, we extend our results to quadratically constrained CQP, and state some open problems.",
 bib2html_errata = "The equation in Theorem 2 is correct, but the proof must be conducted another way. In Theorem 4, a constraint qualification is missing, and the proof also needs more thorough derivation.",
 keywords = "Convex quadratic programming; Interval analysis; Uncertainty modeling",
}

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