In this paper, we discuss how to evaluate the ability of evolutionary many-objective optimization algorithms to find an arbitrarily specified number of non- ...
Abstract—In the evolutionary multi-objective optimization community, algorithm comparison is usually performed under the same population size.
Abstract—In the evolutionary multi-objective optimization community, algorithm comparison is usually performed under the same population size.
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This study addresses a complete and updated review of the literature for multi and many-objective problems and discusses 32 more important algorithms in detail.
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In this paper, we aim to address this problem and develop an effective and efficient evolutionary algorithm (E3A) that can handle various many-objective ...
This paper presents a many-objective evolutionary algorithm, called Adaptive Neighborhood Selection for Many-objective evolutionary algorithm(ANS-MOEA), to deal ...
Each MOEA is evaluated under two optimization scenarios called UEA and reduced UEA in addition to the standard final population scenario. These two scenarios ...
We showed that MOFEA is applicable to different algorithms, and offers improvements over single population algorithms in different situations. Furthermore ...
This paper discusses how to evaluate the ability of evolutionary many-objective optimization algorithms to find an arbitrarily specified number of ...
As can be seen in the ta- ble, using an archive allows a small constant population size, which brings an acceleration of Θ(n) on the expected run- ning time.