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.

中文翻译：

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基于共生生物搜索算法的约束多目标工程设计问题的设计优化

目的

随着计算技术的进步，获得针对工程问题的最佳解决方案已成为各种学科和具有多个目标的实际工程系统中有吸引力的研究主题。因此，旨在通过在折衷之间进行考虑来确保同时优化多个目标。此外，解决这些问题的实际方法主要集中在处理各种复杂的约束上。本文的目的是提出一种基于共生生物搜索（SOS）的算法，该算法可模拟有机体在生态系统中生存和繁殖所采用的共生互惠影响方案，以解决受约束的多目标工程设计问题。

设计/方法/方法

尽管先前已经针对普通的单目标优化问题很好地证明了SOS算法的一般性能，但其对多目标实际工程问题的有效性将决定性能。因此，使用帕累托最优性概念，可以实现SOS算法以获得具有挑战性的约束多目标工程设计问题的最优解。

发现

解决了四个著名的混合约束多目标工程设计问题和一个现实世界中复杂约束多层介电滤波器设计问题，以证明多目标SOS（MOSOS）算法的精度和稳定性。同样，将获得的结果与其他一些著名的元启发式方法进行比较也说明了所提出算法的有效性和鲁棒性。

创意/价值

相对于获得的最佳最终优化设计，成功地证明了MOSOS在具有约束处理方法的具有挑战性的多目标多学科工程设计问题上的算法性能。