Multi-Objective Search Group Algorithm for engineering design problems

Huy, T.H.B. and Nallagownden, P. and Truong, K.H. and Kannan, R. and Vo, D.N. and Ho, N. (2022) Multi-Objective Search Group Algorithm for engineering design problems. Applied Soft Computing, 126. ISSN 15684946

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Abstract

This study proposes a new multi-objective version of the Search Group Algorithm (SGA) called the Multi-Objective Search Group Algorithm (MOSGA). The MOSGA is the combination of the conventional SGA integrated with an elitist non-dominated sorting technique, enabling it to define Pareto optimal solutions via mutation, offspring generation, and selection. The Pareto archive with a selection mechanism is used to preserve and enhance the convergence and diversity of solutions. The MOSGA is validated on twenty-five prominent case studies, including nineteen unconstrained multi-objective benchmark problems, six constrained multi-objective benchmark problems, and five multi-objective engineering design problems to validate its capability and effectiveness. The statistical results are compared to the outcomes of other well-regarded algorithms using the same performance metrics. The comparative results show that MOGSA is robust and superior in handling a wide variety of multi-objective problems. © 2022

Item Type: Article
Additional Information: cited By 6
Uncontrolled Keywords: Benchmarking; Genetic algorithms; Optimal systems; Pareto principle, Benchmark problems; Elitist non-dominated sorting; Engineering design problems; Multi objective; Multi-objectives optimization; Nondominated solutions; Pareto archive; Pareto optimal solutions; Search group algorithm; Sorting techniques, Multiobjective optimization
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 19 Dec 2023 03:22
Last Modified: 19 Dec 2023 03:22
URI: https://khub.utp.edu.my/scholars/id/eprint/16425

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