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Simplified swarm optimization with modular search for the general multi-level redundancy allocation problem in series-parallel systems
Conference paper

Simplified swarm optimization with modular search for the general multi-level redundancy allocation problem in series-parallel systems

Wei-Chang Yeh, Cyuan-Yu Luo, Chyh-Ming Lai, Chi-Ting Hsu, Yuk Ying Chung and Jsen-Shung Lin
2016 IEEE Congress on Evolutionary Computation, CEC 2016, pp.778-784
11/2016

Abstract

Multi-Level problem Redundancy Allocation problem Simplified Swarm Optimization System Reliability Artificial Intelligence Modeling and Simulation Computer Science Applications Control and Optimization
In recent decade, reliability has been an important factor which may affect the performance of the system. In order to enhance the system reliability, redundancy allocation problem (RAP) is becoming an increasingly important tool in the stages of planning, designing, and controlling of systems. Moreover, the multi-level redundancy allocation problem (MRAP) and multiple multi-level redundancy allocation problem (MMRAP) are extensions derived from the redundancy allocation problem (RAP) for practical modeling of real-life problems. However, while formulating the model, the two problems mentioned above have some restrictions which may not deal with real world problem and lost its generality. Therefore, this paper formulates a new kind of MRAP called general multi-level redundancy allocation problem (GMRAP) to break the restrictions and generalize previous problems. Furthermore, a novel algorithm called simplified swarm optimization with modular search (SSO-MS) is proposed to solve the GMRAP in this paper. Finally, the results obtained by SSO-MS are compared with those obtained from genetic algorithm and particle swarm optimization algorithm. The comparative results show that the proposed SSO-MS is promising among three algorithms and demonstrate the effectiveness of the proposed model and method.

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