Effects of Initialization Methods on the Performance of Surrogate-Based Multiobjective Evolutionary Algorithms

Initialization plays a crucial role in surrogate-based multiobjective evolutionary algorithms (MOEAs) when tackling computationally expensive multiobjective optimization problems. During the initialization process, solutions are generated to train surrogate models. Consequently, the accuracy of thes...

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Vydané v:	IEEE Symposium on Computational Intelligence in Multi-Criteria Decision Making s. 933 - 940
Hlavní autori:	Zhang, Jinyuan, Ishibuchi, Hisao, He, Linjun, Nan, Yang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 05.12.2023
Predmet:	Bridges Classification algorithms Computational modeling Evolutionary computation Hypercubes initialization Measurement Multiobjective evolutionary algorithms Optimization surrogate models
ISSN:	2472-8322
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