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Tehnički vjesnik, Vol.22 No.1 Veljača 2015.

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DOI: 10.17559/TV-20130905130612

Boosting the performance of metaheuristics for the MinLA problem using a more discriminating evaluation function

Eduardo Rodriguez-Tello   ORCID icon orcid.org/0000-0002-0333-0633 ; CINVESTAV-Tamaulipas, Information Technology Laboratory, Km. 5.5 Carretera Victoria-Soto La Marina, 87130 Victoria Tamps., Mexico
Jin-Kao Hao   ORCID icon orcid.org/0000-0001-8813-4377 ; LERIA, Université d'Angers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France
Hillel Romero-Monsivais ; CINVESTAV-Tamaulipas, Information Technology Laboratory, Km. 5.5 Carretera Victoria-Soto La Marina, 87130 Victoria Tamps., Mexico

Puni tekst: engleski, pdf (911 KB) str. 11-24 preuzimanja: 257* citiraj
APA
Rodriguez-Tello, E., Hao, J., Romero-Monsivais, H. (2015). Boosting the performance of metaheuristics for the MinLA problem using a more discriminating evaluation function. Tehnički vjesnik, 22(1). doi:10.17559/TV-20130905130612
Puni tekst: hrvatski, pdf (911 KB) str. 11-24 preuzimanja: 115* citiraj
APA
Rodriguez-Tello, E., Hao, J., Romero-Monsivais, H. (2015). Poboljšanje učinaka metaheuristike kod MinLA problema primjenom kritičnije funkcije evaluacije. Tehnički vjesnik, 22(1). doi:10.17559/TV-20130905130612

Sažetak
This paper investigates the role of evaluation function used by metaheuristics for solving combinatorial optimization problems. Evaluation function (EF) is a key component of any metaheuristic algorithm and its design directly influences the performance of such an algorithm. However, the design of more discriminating EFs is somewhat overlooked in the literature. We present in this work the first in-depth analysis of the conventional EF for the Minimum Linear Arrangement (MinLA) problem. The results from this study highlighted its potential drawbacks and led to useful insight and information which guided us to design a new more discerning EF. Its practical usefulness was assessed within three different algorithms: a parameter-free Steepest Descent, an Iterated Local Search and a Tabu Search. The analysis of the data produced by these comparisons showed that the performance of the three adopted approaches could be boosted by using the proposed more discriminating EF.

Ključne riječi
combinatorial optimization; evaluation function; linear arrangement problem; metaheuristics

Hrčak ID: 135059

URI
http://hrcak.srce.hr/135059

[hrvatski]

Posjeta: 595 *