Three types of differential evolution applied to the facility location problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099108" target="_blank" >RIV/61989100:27240/16:86099108 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-33609-1_44" target="_blank" >http://dx.doi.org/10.1007/978-3-319-33609-1_44</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-33609-1_44" target="_blank" >10.1007/978-3-319-33609-1_44</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Three types of differential evolution applied to the facility location problem

Popis výsledku v původním jazyce

Facility location problem is a combinatorial optimization problem with many variants and a number of real-world applications in operations research and industry. A number of exact and approximate methods has been developed to tackle this complex task. Populational nature-inspired metaheuristic optimization methods have been investigated in context of the facility location problem as well. They are able to find excellent problem solutions, but often rely on domain-specific local search and employ heuristic steps. In this work, we study the application of three different flavours of the differential evolution algorithm to a hard variant of the facility location problem. The methods are used as pure metaheuristics without any domain specific knowledge and the efficiency of different optimization strategies they represent is evaluated and compared on a test data set. (C) Springer International Publishing Switzerland 2016.

Název v anglickém jazyce

Three types of differential evolution applied to the facility location problem

Popis výsledku anglicky

Facility location problem is a combinatorial optimization problem with many variants and a number of real-world applications in operations research and industry. A number of exact and approximate methods has been developed to tackle this complex task. Populational nature-inspired metaheuristic optimization methods have been investigated in context of the facility location problem as well. They are able to find excellent problem solutions, but often rely on domain-specific local search and employ heuristic steps. In this work, we study the application of three different flavours of the differential evolution algorithm to a hard variant of the facility location problem. The methods are used as pure metaheuristics without any domain specific knowledge and the efficiency of different optimization strategies they represent is evaluated and compared on a test data set. (C) Springer International Publishing Switzerland 2016.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Mnohoparadigmatické algoritmy dolování z dat založené na vyhledávání, fuzzy technologiích a bio-inspirovaných výpočtech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 450

ISBN

978-3-319-33608-4

ISSN

1615-3871

e-ISSN

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Počet stran výsledku

13

Strana od-do

487-499

Název nakladatele

Springer

Místo vydání

Basel

Místo konání akce

Soči

Datum konání akce

16. 5. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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