A hybrid method to solve reliability-cost-oriented bi-objective machine configuration problem for a flow shop system

Cheng Ta Yeh, Louis Cheng Lu Yeng, Yi Kuei Lin*, Yu Lun Chao

*此作品的通信作者

研究成果: Article同行評審

摘要

Machine configuration is a crucial strategic decision in designing a flow shop system (FSS) and directly affects its performance. This involves selecting device suppliers and determining the number of machines to be configured. This study addresses a bi-objective optimization problem for an FSS that considers repair actions and aims to determine the most suitable machine configuration that balances the production reliability and purchase cost. A nondominated sorting genetic algorithm II (NSGA-II) is used to determine all the Pareto solutions. The technique for order preference by similarity to an ideal solution is then used to identify a compromise alternative. It is necessary to assess the production reliability of any machine configuration identified by the NSGA-II. The FSS under the machine configuration is modeled as a multistate flow shop network, and Absorbing Markov Chain and Recursive Sum of Disjoint Products are integrated into the NSGA-II for reliability evaluation. The experimental results of solar cell manufacturing demonstrate the applicability of the proposed hybrid method and validate the efficiency of the NSGA-II compared with an improved strength Pareto evolutionary algorithm.

原文English
頁(從 - 到)643-669
頁數27
期刊Annals of Operations Research
340
發行號1
DOIs
出版狀態Published - 9月 2024

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