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Feasible corrector-predictor interior-point algorithm for P* (k)-linear complementarity problems based on a new search direction
ID Darvay, Zsolt (Author), ID Illés, Tibor (Author), ID Povh, Janez (Author), ID Rigó, Petra Renáta (Author)

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Abstract
We introduce a new feasible corrector-predictor (CP) interior-point algorithm (IPA), which is suitable for solving linear complementarity problem (LCP) with P*(k)-matrices. We use the method of algebraically equivalent transformation (AET) of the nonlinear equation of the system which defines the central path. The AET is based on the function [varphi](t) = t - [sqrt]t and plays a crucial role in the calculation of the new search direction. We prove that the algorithm has O((1 + 2k) [sqrt]n log 9n[micro]0/8[epsilon]) iteration complexity, where k is an upper bound of the handicap of the input matrix. To the best of our knowledge, this is the first CP IPA for P*(k)-LCPs which is based on this search direction. We implement the proposed CP IPA in the C++ programming language with specific parameters and demonstrate its performance on three families of LCPs. The first family consists of LCPs with P*(k)-matrices. The second family of LCPs has the P-matrix defined by Csizmadia. Eisenberg-Nagy and de Klerk [Math. Program., 129 (2011), pp. 383-402] showed that the handicap of this matrix should be at least 2[sup]2n-8 - 1/4 . Namely, from the known complexity results for P*(k)-LCPs it might follow that the computational performance of IPAs on LCPs with the matrix defined by Csizmadia could be very poor. Our preliminary computational study shows that an implemented variant of the theoretical version of the CP IPA (Algorithm 4.1) presented in this paper, finds a [epsilon]-approximate solution for LCPs with the Csizmadia matrix in a very small number of iterations. The third family of problems consists of the LCPs related to the copositivity test of 88 matrices from [C. Brás, G. Eichfelder, and J. Júdice, Comput. Optim. Appl., 63 (2016), pp. 461-493]. For each of these matrices we create a special LCP and try to solve it using our IPA. If the LCP does not have a solution, then the related matrix is strictly copositive, otherwise it is on the boundary or outside the copositive cone. For these LCPs we do not know whether the underlying matrix is P*(k) or not, but we could reveal the real copositivity status of the input matrices in 83 out of 88 cases (accuracy _> 94%). The numerical test shows that our CP IPA performs well on the sets of test problems used in the paper.

Language:English
Keywords:corrector-predictor interior-point algorithm, P*(k)-linear complementarity problem, new search direction, polynomial iteration complexity, copositivity test
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Author Accepted Manuscript
Year:2020
Number of pages:Str. 2628-2658
Numbering:Vol. 30, iss. 3
PID:20.500.12556/RUL-121361 This link opens in a new window
UDC:519.6(045)
ISSN on article:1052-6234
DOI:10.1137/19M1248972 This link opens in a new window
COBISS.SI-ID:31245059 This link opens in a new window
Publication date in RUL:06.10.2020
Views:836
Downloads:321
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Secondary language

Language:Slovenian
Keywords:korekcijsko napovedovalne metode notranjih točk, P*(k)-problem linearne komplementarnosti, nova iskalna smer, polinomska časovna zahtevnost, test kopozitivnosti

Projects

Funder:ARRS - Slovenian Research Agency
Project number:J1-8155
Name:ZLIVANJE BIOMEDICINSKIH PODATKOV Z UPORABO NENEGATIVNE MATRIČNETRI-FAKTORIZACIJE

Funder:ARRS - Slovenian Research Agency
Project number:N1-0057
Name:Visoko zmogljiv reševalec za binarne kvadratične probleme

Funder:ARRS - Slovenian Research Agency
Project number:N1-0071
Name:Razširitev algoritmov prvega in drugega reda za izbrane razrede optimizacijskih problemov s ciljem rešiti računsko zahtevne industrijske probleme

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