Multi-objective optimization of series-parallel system with mixed subsystems failure dependencies using NSGA-II and MOHH

IF 2.1 4区 工程技术
Mohamed Arezki Mellal
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引用次数: 0

Abstract

In complex systems, failure dependencies play a crucial role in determining their overall performance. This paper explores the multi-objective optimization of series-parallel systems with mixed failure dependencies. By optimizing system cost and availability, the study aims to identify the most efficient redundancy and repair strategies. Two optimization algorithms, the non-dominated sorting genetic algorithm II (NSGA-II) and a novel multi-objective algorithm named the multi-objective hoopoe heuristic (MOHH), are utilized alongside constraint handling techniques to produce Pareto fronts. These fronts illustrate the trade-offs between cost and availability. Additionally, a fuzzy decision method is utilized to determine the best compromise solutions from each optimization technique. Comparing the results, NSGA-II consistently outperforms MOHH in providing better compromise solutions across five independent runs. However, MOHH demonstrates a better standard deviation in its performance.
利用 NSGA-II 和 MOHH 对具有混合子系统失效依赖性的串并联系统进行多目标优化
在复杂系统中,故障依赖性对其整体性能起着至关重要的作用。本文探讨了具有混合故障依赖性的串并联系统的多目标优化问题。通过优化系统成本和可用性,该研究旨在确定最有效的冗余和修复策略。本文采用了两种优化算法,即非支配排序遗传算法 II(NSGA-II)和一种名为多目标鵖启发式(MOHH)的新型多目标算法,并利用约束处理技术生成帕累托前沿。这些前沿说明了成本和可用性之间的权衡。此外,还利用模糊决策法来确定每种优化技术的最佳折衷方案。比较结果发现,在五次独立运行中,NSGA-II 在提供更好的折衷解决方案方面始终优于 MOHH。不过,MOHH 的性能标准偏差更大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advances in Mechanical Engineering
Advances in Mechanical Engineering Engineering-Mechanical Engineering
自引率
4.80%
发文量
353
期刊介绍: Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering
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