Behavior of Multiobjective Evolutionary Algorithms on Many-Objective Knapsack Problems

We examine the behavior of three classes of evolutionary multiobjective optimization (EMO) algorithms on many-objective knapsack problems. They are Pareto dominance-based, scalarizing function-based, and hypervolume-based algorithms. NSGA-II, MOEA/D, SMS-EMOA, and HypE are examined using knapsack pr...

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Vydané v:	IEEE transactions on evolutionary computation Ročník 19; číslo 2; s. 264 - 283
Hlavní autori:	Ishibuchi, Hisao, Akedo, Naoya, Nojima, Yusuke
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.04.2015
Predmet:	Approximation algorithms Pareto optimization Search problems Sociology Vectors many-objective problems Evolutionary many-objective optimization evolutionary multiobjective optimization (EMO)
ISSN:	1089-778X, 1941-0026
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