A Stable Large-Scale Multiobjective Optimization Algorithm with Two Alternative Optimization Methods

Autor: Tianyu Liu, Junjie Zhu, Lei Cao
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Entropy, Vol 25, Iss 4, p 561 (2023)
Druh dokumentu: article
ISSN: 25040561
1099-4300
DOI: 10.3390/e25040561
Popis: For large-scale multiobjective evolutionary algorithms based on the grouping of decision variables, the challenge is to design a stable grouping strategy to balance convergence and population diversity. This paper proposes a large-scale multiobjective optimization algorithm with two alternative optimization methods (LSMOEA-TM). In LSMOEA-TM, two alternative optimization methods, which adopt two grouping strategies to divide decision variables, are introduced to efficiently solve large-scale multiobjective optimization problems. Furthermore, this paper introduces a Bayesian-based parameter-adjusting strategy to reduce computational costs by optimizing the parameters in the proposed two alternative optimization methods. The proposed LSMOEA-TM and four efficient large-scale multiobjective evolutionary algorithms have been tested on a set of benchmark large-scale multiobjective problems, and the statistical results demonstrate the effectiveness of the proposed algorithm.
Databáze: Directory of Open Access Journals
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