Hybrid PSO-GWO algorithm for reliability redundancy allocation problem with Cold Standby Strategy

被引:14
|
作者
Bhandari, Ashok Singh [1 ,2 ]
Kumar, Akshay [2 ]
Ram, Mangey [3 ,4 ,5 ]
机构
[1] Graphic Era Univ, Dept Math, Dehra Dun, Uttarakhand, India
[2] Graphic Era Hill Univ, Dept Math, Dehra Dun, Uttarakhand, India
[3] Graphic Era Hill Univ, Dept Math Comp Sci & Engn, Dehra Dun, Uttarakhand, India
[4] Peter Great St Petersburg Polytech Univ, Inst Adv Mfg Technol, St Petersburg, Russia
[5] Graphic Era Univ, Dept Math Comp Sci & Engn, Dehra Dun, Uttarakhand, India
关键词
Cold standby; GWO; HPSGWO; PSO; reliability redundancy allocation problem; SERIES-PARALLEL SYSTEMS; SWARM OPTIMIZATION ALGORITHM; GENETIC ALGORITHMS; ANT COLONY; MULTIOBJECTIVE OPTIMIZATION; DESIGN; SEARCH; CHOICE;
D O I
10.1002/qre.3243
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Reliability allocation for components, redundancy allocation, and reliability redundancy allocation are of great significance for system reliability designing. Generally, standby redundancy gives higher reliability for any system than active redundancy, but standby redundancy has more complex modeling than active redundancy. Cold standby strategy is one of the most consistently applied procedures to accomplish high-reliability necessity, where backups are performed to guarantee that a backup part can take control over the undertaking successfully when the currently working fizzles. Considering the fact that components may fail during the switching process from standby to active, the impact of an imperfect switch is also applied in the system. In this work, a new hybrid GWO-PSO(HPSGWO) algorithm, based on Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), is presented to solve the cold-standby reliability redundancy allocation problem (RRAP). The RRAP is a popular mixed integer nonlinear programming issue in a system plan that necessitates that the reliability target is set to fulfill the resource utilization requirement. Four contextual analyses are examined to feature the applicability of the proposed algorithm. The outcomes are compared with those obtained from PSO and GWO.
引用
收藏
页码:115 / 130
页数:16
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