Analysis of velocity calculation methods in binary PSO on maintenance scheduling

Fatih Camci
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引用次数: 10

Abstract

Even though binary optimization in Genetic Algorithm has been studied extensively, Binary Particle Swarm Optimization (BPSO) methods are relatively new in the literature. There are several binary PSO methods proposed in the literature. Firstly, binary PSO was presented by the father of the PSO method. Then several other methods have been proposed claiming better results. In this work, we analyzed these BPSO methods on maintenance scheduling problem for condition based maintenance system. Evaluation of these methods revealed that their difference mainly focuses on the calculation of velocity vector. Thus, we focus on/compare different velocity calculation methods in BPSO on maintenance scheduling problem in Condition Based Maintenance, which has been presented with Genetic Algorithm in our early work. The tradeoff between maintenance and failure is quantified in risk as the objective function to be minimized.
基于二元粒子群算法的维修调度速度计算方法分析
尽管遗传算法中的二进制优化问题已经得到了广泛的研究,但二进制粒子群优化(BPSO)方法在文献中相对较新。文献中提出了几种二值粒子群算法。首先,由粒子群算法之父提出了二值粒子群算法。然后提出了其他几种方法,声称效果更好。本文对基于状态的维修系统的维修调度问题进行了分析。对这些方法的评价表明,它们的差异主要集中在速度矢量的计算上。因此,在基于状态的维修调度问题上,我们重点研究/比较了BPSO中不同的速度计算方法,该方法在我们早期的工作中已经用遗传算法提出。将维护与故障之间的权衡以风险作为最小化目标函数进行量化。
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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