A Birnbaum-importance based genetic local search algorithm for component assignment problems

Qingzhu Yao, Xiaoyan Zhu () and Way Kuo

Annals of Operations Research, 2014, vol. 212, issue 1, 185-200

Abstract: This paper considers the component assignment problem (CAP) of finding the optimal assignment of n available components to n positions in a system such that the system reliability is maximized. To solve the CAP, an important type of problems in reliability, we propose a Birnbaum-importance based genetic local search (BIGLS) algorithm in which a local search using the Birnbaum importance is embedded into the genetic algorithm. This paper presents comprehensive numerical tests to compare the performance of the BIGLS with a general genetic algorithm and a Birnbaum-importance based two-stage heuristic. The testing results show that the BIGLS is robust (with respect to its random operations) and effective, and outperforms two benchmark methods in terms of solution quality. It demonstrates the effectiveness of embedding the Birnbaum importance in the local search under the genetic evolutionary mechanism. Copyright Springer Science+Business Media, LLC 2014

Keywords: Genetic algorithm; Reliability; Local search; Component assignment problem; Birnbaum importance (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (17)

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DOI: 10.1007/s10479-012-1223-1

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