Fitness landscape analysis of hyper-heuristic transforms for the vertex cover problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10333621" target="_blank" >RIV/00216208:11320/16:10333621 - isvavai.cz</a>

Výsledek na webu

<a href="http://ceur-ws.org/Vol-1649/179.pdf" target="_blank" >http://ceur-ws.org/Vol-1649/179.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Fitness landscape analysis of hyper-heuristic transforms for the vertex cover problem

Popis výsledku v původním jazyce

Hyper-heuristics have recently proved efficient in several areas of combinatorial search and optimiza- tion, especially scheduling. The basic idea of hyper- heuristics is based on searching for search-strategy. In- stead of traversing the solution-space, the hyper-heuristic traverses the space of algorithms to find or construct an algorithm best suited for the given problem instance. The observed efficiency of hyper-heuristics is not yet fully ex- plained on the theoretical level. The leading hypothesis suggests that the fitness landscape of the algorithm-space is more favorable to local search techniques than the orig- inal space. In this paper, we analyse properties of fitness landscapes of the problem of minimal vertex cover. We focus on prop- erties that are related to efficiency of metaheuristics such as locality and fitness-distance correlation. We compare properties of the original space and the algorithm space trying to verify the hypothesis explaining hyper-heuristics performance. Our analysis shows that the hyper-heuristic- space really has some more favorable properties than the original space.

Název v anglickém jazyce

Fitness landscape analysis of hyper-heuristic transforms for the vertex cover problem

Popis výsledku anglicky

Hyper-heuristics have recently proved efficient in several areas of combinatorial search and optimiza- tion, especially scheduling. The basic idea of hyper- heuristics is based on searching for search-strategy. In- stead of traversing the solution-space, the hyper-heuristic traverses the space of algorithms to find or construct an algorithm best suited for the given problem instance. The observed efficiency of hyper-heuristics is not yet fully ex- plained on the theoretical level. The leading hypothesis suggests that the fitness landscape of the algorithm-space is more favorable to local search techniques than the orig- inal space. In this paper, we analyse properties of fitness landscapes of the problem of minimal vertex cover. We focus on prop- erties that are related to efficiency of metaheuristics such as locality and fitness-distance correlation. We compare properties of the original space and the algorithm space trying to verify the hypothesis explaining hyper-heuristics performance. Our analysis shows that the hyper-heuristic- space really has some more favorable properties than the original space.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

8

Strana od-do

179-186

Název nakladatele

CEUR-WS

Místo vydání

Neuveden

Místo konání akce

Tatranské Matliare, Slovakia

Datum konání akce

15. 9. 2016

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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