A novel discrete bat algorithm for heterogeneous redundancy allocation of multi-state systems subject to probabilistic common-cause failure

Date

2020-11-20

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Elsevier

Type

Article

Peer reviewed

Yes

Abstract

This paper focuses on a heterogeneous redundancy allocation problem (RAP) for multi-state series-parallel systems subject to probabilistic common-cause failure and proposes a novel discrete bat algorithm to solve it. Although abundant research studies have been published for solving multi-state RAPs, few of them have studied probabilistic common cause failure, which motivates this paper. Due to the insufficient data of components, an interval-valued universal generating function is utilized to evaluate the availability of components and the whole system. The challenge of solving this kind of RAPs lies in not only the reliability estimation, but also the solution method. This paper presents a novel discrete bat algorithm (BA) for effectively dealing with the proposed RAP and alleviating the premature convergence of BA. Two main features of the adaptation are Hamming distance-based bat movement (HDBM) and Q learning-based local search (QLLS). HDBM transfers the Hamming distance between the current bat and the best bat in the swarm to the movement rate. Then, QLLS utilizes Q-learning to adjust the local search strategies dynamically during the iterations. The computational results from extensive experiments demonstrate that the proposed algorithm is powerful, which is more efficient than other state-of-the-arts on this sort of problems.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Keywords

Heterogeneous redundancy allocation problem, Multi-state system, Probabilistic common-cause failure, Bat algorithm, Hamming distance, Q learning, Local search

Citation

Y. Xu, D. Pi, S. Yang, and Y. Chen. (2021) A novel discrete bat algorithm for heterogeneous redundancy allocation of multi-state systems subject to probabilistic common-cause failure. Reliability Engineering and System Safety, 208, 107338

Rights

Research Institute

Institute of Artificial Intelligence (IAI)