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Multi-Objective Search Group Algorithm for engineering design problems
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DOI：10.1016/j.asoc.2022.109287.png)
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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. (C) 2022 Elsevier B.V. All rights reserved.
Keyword:
Engineering design problems
Multi-objective optimization
Non-dominated solution
Pareto optimal solution
Search Group Algorithm
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
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