Data Clustering of Solutions for Multiple Objective System Reliability Optimization Problems

2007 ◽  
Vol 4 (2) ◽  
pp. 191-210 ◽  
Author(s):  
Heidi A. Taboada ◽  
David W. Coit
Keyword(s):  
System Reliability ◽  
Data Clustering ◽  
Optimization Problems ◽  
Multiple Objective ◽  
Reliability Optimization ◽  
Objective System ◽  
System Reliability Optimization

scholarly journals An adaptive particle swarm optimization method for multi-objective system reliability optimization

2019 ◽  
Vol 233 (6) ◽  
pp. 990-1001 ◽  
Author(s):  
Mohamed Arezki Mellal ◽  
Enrico Zio
Keyword(s):  
Particle Swarm Optimization ◽  
System Reliability ◽  
Particle Swarm ◽  
Superior Performance ◽  
Reliability Optimization ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Multi Objective ◽  
Objective System ◽  
System Reliability Optimization

Multi-objective system reliability optimization has attracted the attention of several researchers, due to its importance in industry. In practice, the optimization regards multiple objectives, for example, maximize the reliability, minimize the cost, weight, and volume. In this article, an adaptive particle swarm optimization is presented for multi-objective system reliability optimization. The approach uses a Lévy flight for some particles of the swarm, for avoiding local optima and insuring diversity in the exploration of the search space. The multi-objective problem is converted to a single-objective problem by resorting to the weighted-sum method and a penalty function is implemented to handle the constraints. Nine numerical case studies are presented as benchmark problems for comparison; the results show that the proposed approach has superior performance than a standard particle swarm optimization.

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