A genetic algorithm for solving a maintenance model in a FMS

Chinho Lin; Jong Mau Yeh; Jieh Rern Ding

doi:10.1080/002077200291037

A genetic algorithm for solving a maintenance model in a FMS

Chinho Lin, Jong Mau Yeh, Jieh Rern Ding

Institute of Information Management

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6 Citations (Scopus)

Abstract

Maintenance float problems in a flexible manufacturing system structure are intractable. Therefore, there is a need for an enumerative search method to solve such problems. This study presents a novel genetic algorithm to search for the optimal float and capacity of repair stations for FMS maintenance float systems. The proposed algorithm is operated under a feasible set of failure rates to investigate how its performance dominates the enumerative search algorithm. Experimental results indicate that the genetic algorithm is more promising than the enumerative search algorithm in searching for the best approximate solution and in minimizing the execution time.

Original language	English
Pages (from-to)	449-456
Number of pages	8
Journal	International Journal of Systems Science
Volume	31
Issue number	4
DOIs	https://doi.org/10.1080/002077200291037
Publication status	Published - 2000 Jan 1

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Theoretical Computer Science
Computer Science Applications

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10.1080/002077200291037

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N2 - Maintenance float problems in a flexible manufacturing system structure are intractable. Therefore, there is a need for an enumerative search method to solve such problems. This study presents a novel genetic algorithm to search for the optimal float and capacity of repair stations for FMS maintenance float systems. The proposed algorithm is operated under a feasible set of failure rates to investigate how its performance dominates the enumerative search algorithm. Experimental results indicate that the genetic algorithm is more promising than the enumerative search algorithm in searching for the best approximate solution and in minimizing the execution time.

AB - Maintenance float problems in a flexible manufacturing system structure are intractable. Therefore, there is a need for an enumerative search method to solve such problems. This study presents a novel genetic algorithm to search for the optimal float and capacity of repair stations for FMS maintenance float systems. The proposed algorithm is operated under a feasible set of failure rates to investigate how its performance dominates the enumerative search algorithm. Experimental results indicate that the genetic algorithm is more promising than the enumerative search algorithm in searching for the best approximate solution and in minimizing the execution time.

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A genetic algorithm for solving a maintenance model in a FMS

Abstract

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