An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86097115" target="_blank" >RIV/61989100:27240/11:86097115 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5949696" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5949696</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CEC.2011.5949696" target="_blank" >10.1109/CEC.2011.5949696</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance

Popis výsledku v původním jazyce

This paper presents a new Multiobjective Evolutionary Algorithm (MOEA) based on decomposition, with fuzzy dominance (MOEA/DFD). The algorithm introduces a fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method only when one of the solutions fails to dominate the other in terms of a fuzzy dominance level. The diversity is maintained through the uniformly distributed weight vectors. In addition, Dynamic Resource Allocation (DRA) is used to distribute the computational effort based on the utilities of the individuals. To assess the performance of the proposed algorithm, experiments were conducted on two general benchmarks and ten unconstrained benchmark problems taken from the competition on real parameter MOEAs held under the 2009 IEEE Congress on Evolutionary Computation (CEC). As per the IGD metric, MOEA/DFD outperforms other major MOEAs in most cases. (C) 2011 IEEE.

Název v anglickém jazyce

An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance

Popis výsledku anglicky

This paper presents a new Multiobjective Evolutionary Algorithm (MOEA) based on decomposition, with fuzzy dominance (MOEA/DFD). The algorithm introduces a fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method only when one of the solutions fails to dominate the other in terms of a fuzzy dominance level. The diversity is maintained through the uniformly distributed weight vectors. In addition, Dynamic Resource Allocation (DRA) is used to distribute the computational effort based on the utilities of the individuals. To assess the performance of the proposed algorithm, experiments were conducted on two general benchmarks and ten unconstrained benchmark problems taken from the competition on real parameter MOEAs held under the 2009 IEEE Congress on Evolutionary Computation (CEC). As per the IGD metric, MOEA/DFD outperforms other major MOEAs in most cases. (C) 2011 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: Nové metody přenosu dat založené na turbo kódech</a><br>

Návaznosti

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

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

2011 IEEE Congress of Evolutionary Computation, CEC 2011

ISBN

978-1-4244-7834-7

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

765-772

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

New Orleans

Datum konání akce

5. 6. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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