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A symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems

Deniz Ustun (Department of Computer Engineering, Faculty of Engineering, Tarsus University, Tarsus, Turkey)
Serdar Carbas (Department of Civil Engineering, Faculty of Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey)
Abdurrahim Toktas (Department of Electrical and Electronics Engineering, Faculty of Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey)

Engineering Computations

ISSN: 0264-4401

Article publication date: 8 July 2020

Issue publication date: 8 February 2021

267

Abstract

Purpose

In line with computational technological advances, obtaining optimal solutions for engineering problems has become attractive research topics in various disciplines and real engineering systems having multiple objectives. Therefore, it is aimed to ensure that the multiple objectives are simultaneously optimized by considering them among the trade-offs. Furthermore, the practical means of solving those problems are principally concentrated on handling various complicated constraints. The purpose of this paper is to suggest an algorithm based on symbiotic organisms search (SOS), which mimics the symbiotic reciprocal influence scheme adopted by organisms to live on and breed within the ecosystem, for constrained multi-objective engineering design problems.

Design/methodology/approach

Though the general performance of SOS algorithm was previously well demonstrated for ordinary single objective optimization problems, its efficacy on multi-objective real engineering problems will be decisive about the performance. The SOS algorithm is, hence, implemented to obtain the optimal solutions of challengingly constrained multi-objective engineering design problems using the Pareto optimality concept.

Findings

Four well-known mixed constrained multi-objective engineering design problems and a real-world complex constrained multilayer dielectric filter design problem are tackled to demonstrate the precision and stability of the multi-objective SOS (MOSOS) algorithm. Also, the comparison of the obtained results with some other well-known metaheuristics illustrates the validity and robustness of the proposed algorithm.

Originality/value

The algorithmic performance of the MOSOS on the challengingly constrained multi-objective multidisciplinary engineering design problems with constraint-handling approach is successfully demonstrated with respect to the obtained outperforming final optimal designs.

Keywords

Citation

Ustun, D., Carbas, S. and Toktas, A. (2021), "A symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems", Engineering Computations, Vol. 38 No. 2, pp. 632-658. https://doi.org/10.1108/EC-03-2020-0140

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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