A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems. (October 2015)

• Record Type: Journal Article
• Authors: Huang, Chia-Ling
• Is Part Of: Reliability engineering & system safety. Volume 142(2015:Oct.)
• Page Start: 221
• Page End: 230
• Publication Date: 2015-10
• Subjects: Reliability -- Redundancy allocation problem -- PSO -- SSO -- Mixed-integer nonlinear programming; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2015.06.002
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. Highlights: This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. Four systems are introduced and the results demonstrate the PSSO performs particularly well.