A hybrid success history-based adaptive differential evolution and manta ray foraging optimization for multi-objective truss optimization problems

Zhong, Changting, Li, Gang ORCID: https://orcid.org/0000-0001-6326-8133, Meng, Zeng, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133, He, Wanxin and Zhao, Kai 2022. A hybrid success history-based adaptive differential evolution and manta ray foraging optimization for multi-objective truss optimization problems. Presented at: 2022 Annual Conference of the UK Association for Computational Mechanics (UKACM), Nottingham, England, 20-22 April 2022.

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Abstract

In this paper, a hybrid multi-objective metaheuristic algorithm based on the manta ray foraging optimization (MRFO) and the success history-based parameter adaptive differential evolution (SHADE) is developed to solve multi-objective truss optimization problems, called MO-SHADE-MRFO. SHADE is a variant of differential evolution with high performance in solving optimization problems, and MRFO is a novel metaheuristic algorithm inspired from the behavior of manta rays. In the proposed algorithm, the updating mechanism of MRFO is embedded into the SHADE, to enhance global convergence of SHADE for multi-objective truss optimization problems. The design problem is to minimize both structural mass and compliance subjected to stress constraints. Six benchmark truss optimization problems, including 10-bar, 25-bar, 37-bar, 120-bar, 200-bar and 942-bar trusses, are utilized to test the effectiveness of the proposed algorithm. The performance of the proposed algorithm is compared with nine state-of-the-art algorithms, in terms of metrics including hypervolume, inverted generational distance, and spacing-to-extent. The experiment results demonstrate that the proposed algorithm can obtain the best statistical values of metrics and the lowest standard deviation values in most test problems, which is more accurate than the compared algorithms. The Pareto solutions obtained by the proposed algorithm are well-distributed and smooth in each problem.

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Date of First Compliant Deposit:	5 April 2022
Date of Acceptance:	26 January 2022
Last Modified:	06 Jan 2024 04:32
URI:	https://orca.cardiff.ac.uk/id/eprint/149350

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