A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

doi:10.1016/j.ress.2016.09.006

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A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

2017-01-01

PRE

Ahmad Attar

Sadigh Raissi

Kaveh Khalili‐Damghani *

DOI：10.1016/j.ress.2016.09.006

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Abstract

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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.

Keywords:

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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