This article presents a new two-stage stochastic model for the simultaneous optimization of component test plan and redundancy allocation. The optimal number of tests is determined for each component of the system in the first stage, and the system redundancy configuration is optimized in the second stage, after the realization of the system working condition. Scenario analysis is used for modeling variations in working conditions. A multiobjective reliability problem is formulated for series-parallel systems, and the allocation of redundancy is optimized by a genetic algorithm. The results of the feedback control system demonstrate the performance of the proposed model.

A Two-Stage Stochastic Programming Model of Component Test Plan and Redundancy Allocation for System Reliability Optimization

Zio E.
2021-01-01

Abstract

This article presents a new two-stage stochastic model for the simultaneous optimization of component test plan and redundancy allocation. The optimal number of tests is determined for each component of the system in the first stage, and the system redundancy configuration is optimized in the second stage, after the realization of the system working condition. Scenario analysis is used for modeling variations in working conditions. A multiobjective reliability problem is formulated for series-parallel systems, and the allocation of redundancy is optimized by a genetic algorithm. The results of the feedback control system demonstrate the performance of the proposed model.
2021
Genetic algorithm (GA)
redundancy allocation
test plan
two-stage stochastic programming (TSSP)
uncertainty in working condition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1181158
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