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A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems
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DOI：10.1016/j.ress.2016.09.006.png)
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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.
Keyword:
Availability-redundancy allocation
Simulation based optimization (SBO)
Multi-state systems
Distribution-free failure/repair time
Non-dominated sorting genetic algorithm
Repairable systems
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