Optimizing redundancy allocation problem with repairable components based on the Monte Carlo simulation

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Shahriari Mohammadreza; Peyman Hajizadeh; Zaretalab Arash

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS Year:2024 | Volume:15 | Issue:2 Page(s): 115-124

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Information Journal Paper

Title

Optimizing redundancy allocation problem with repairable components based on the Monte Carlo simulation

Author(s)

Shahriari Mohammadreza | Peyman Hajizadeh | Zaretalab Arash | Issue Writer Certificate

Keywords

Reliability

Redundancy allocation problem

k-out-of-n sub-systems

Common Cause Failures

Genetic algorithm

Abstract

The optimization of Reliability is crucial across various engineering domains. The Redundancy allocation problem (RAP) is among the key challenges within Reliability. This study introduces an RAP incorporating repairable components and a k-out-of-n sub-systems structure. The objective function aims to maximize system Reliability while adhering to cost and weight constraints. The goal is to determine the optimal number of components for each subsystem, including the appropriate allocation of repairmen to each subsystem. Given that this model is classified as an Np-Hard problem, we employed a Genetic algorithm (GA) to solve the proposed model. Additionally, response surface methodology (RSM) was utilized to fine-tune the algorithm parameters. To calculate the Reliability of each subsystem, as well as the overall system Reliability, a Monte Carlo simulation was employed. Lastly, a numerical example was solved to assess the algorithm's performance.

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