A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems
| Autor: | Ahmad Attar, Kaveh Khalili-Damghani, Sadigh Raissi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Engineering Mathematical optimization 021103 operations research Multi state business.industry Hot spare 0211 other engineering and technologies Evolutionary algorithm Pareto principle 02 engineering and technology Industrial and Manufacturing Engineering Evolutionary computation Reliability engineering 020901 industrial engineering & automation Simulation-based optimization Redundancy (engineering) Probability distribution Safety Risk Reliability and Quality business |
| Zdroj: | Reliability Engineering & System Safety. 157:177-191 |
| ISSN: | 0951-8320 |
| DOI: | 10.1016/j.ress.2016.09.006 |
| Popis: | A simulation-based optimization (SBO) method is proposed to handle multi-objective joint availability-redundancy allocation problem (JARAP). Here, there is no emphasis on probability distributions of time to failures and repair times for multi-state multi-component series-parallel configuration under active, cold and hot standby strategies. Under such conditions, estimation of availability is not a trivial task. First, an efficient computer simulation model is proposed to estimate the availability of the aforementioned system. Then, the estimated availability values are used in a repetitive manner as parameter of a two-objective joint availability-redundancy allocation optimization model through SBO mechanism. The optimization model is then solved using two well-known multi-objective evolutionary computation algorithms, i.e., non-dominated sorting genetic algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA2). The proposed SBO approach is tested using non-exponential numerical example with multi-state repairable components. The results are presented and discussed through different demand scenarios under cold and hot standby strategies. Furthermore, performance of NSGA-II and SPEA2 are statistically compared regarding multi-objective accuracy, and diversity metrics. |
| Databáze: | OpenAIRE |
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