A GA methodology for the scheduling of yarn-dyed textile production

Authors:
Hsi-Mei Hsu;Yai Hsiung;Ying-Zhi Chen;Muh-Cherng Wu
Affiliations:
Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC;Department of Information Management, Ta Hwa Institute of Technology, Hsin-Chu, Taiwan, ROC;Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC;Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

This paper presents a scheduling approach for yarn-dyed textile manufacturing. The scheduling problem is distinct in having four characteristics: multi-stage production, sequence-dependent setup times, hierarchical product structure, and group-delivery (a group of jobs pertaining to a particular customer order must be delivered together), which are seldom addressed as a whole in literature. The scheduling objective is to minimize the total tardiness of customer orders. The problem is formulated as a mixed integer programming (MIP) model, which is computationally extensive. To reduce the problem complexity, we decomposed the scheduling problem into a sequence of sub-problems. Each sub-problem is solved by a genetic algorithm (GA), and an iteration of solving the whole sequence of sub-problems is repeated until a satisfactory solution has been obtained. Numerical experiment results indicated that the proposed approach significantly outperforms the EDD (earliest due date) scheduling method-currently used in the yarn-dyed textile industry.