Redundancy allocation for multi-state systems using physical programming and genetic algorithms

Zhigang Tian and Ming J. Zuo

Reliability Engineering and System Safety, 2006, vol. 91, issue 9, 1049-1056

Abstract: This paper proposes a multi-objective optimization model for redundancy allocation for multi-state series–parallel systems. This model seeks to maximize system performance utility while minimizing system cost and system weight simultaneously. We use physical programming as an effective approach to optimize the system structure within this multi-objective optimization framework. The physical programming approach offers a flexible and effective way to address the conflicting nature of these different objectives. Genetic algorithm (GA) is used to solve the proposed physical programming-based optimization model due to the following three reasons: (1) the design variables, the number of components of each subsystems, are integer variables; (2) the objective functions in the physical programming-based optimization model do not have nice mathematical properties, and thus traditional optimization approaches are not suitable in this case; (3) GA has good global optimization performance. An example is used to illustrate the flexibility and effectiveness of the proposed physical programming approach over the single-objective method and the fuzzy optimization method.

Keywords: Multi-state series–parallel system; Multi-objective optimization; Genetic algorithm; Physical programming; Fuzzy optimization (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:9:p:1049-1056

DOI: 10.1016/j.ress.2005.11.039

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