Simplified swarm optimization for repairable redundancy allocation problem in multi-state systems with bridge topology

• Published in: 2016 International Joint Conference on Neural Networks (IJCNN) pp. 3935 - 3941
• Main Authors: Wei-Chang Yeh, Siang-Tai Wang, Chyh-Ming Lai, Yen-Cheng Huang, Yuk Ying Chung, Jsen-Shung Lin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2016
• Subjects: Bridges; Genetic algorithms; Maintenance engineering; multi-state systems; Particle swarm optimization; Redundancy; redundancy allocation problem; repairable components; Resource management; simplified swarm optimization; universal generating function
• ISSN: 2161-4407
• DOI: 10.1109/IJCNN.2016.7727710

In recent decades, the redundancy allocation problem (RAP) is becoming an increasingly important issue in the initial stages of planning, designing, and controlling of systems. However, RAP in multi-state system (MSSs) still has some restrictions that components have only two performances: perfect functionality and complete failure. Therefore, this paper formulates a new kind of RAP called repairable redundancy allocation problem (RRAP) in multi-state systems (RRAP in MSSs) to break the restrictions. RRAP in MSSs is nearer to reality and widespread in many critical systems. RRAP in MSSs is not only an NP-hard problem, but also a nonlinear integer optimization problem. In order to deal with RRAP in MSSs in a reasonable time, this paper employs an optimization method of soft computing called simplified swarm optimization (SSO). Finally, the results obtained by SSO have been compared with that obtained from genetic algorithm (GA). Computational results show that the SSO is very competitive and effective in this problem.