Paper Info
Title
A GA methodology for the scheduling of yarn-dyed textile production
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.
Year
DOI
Venue
2009
10.1016/j.eswa.2009.04.075
Expert Syst. Appl.
Keywords
Field
DocType
customer order,sequence-dependent setup,yarn-dyed textile industry,ga methodology,scheduling problem,scheduling objective,genetic algorithm,particular customer order,scheduling,scheduling approach,whole sequence,group-delivery,problem complexity,yarn-dyed textile manufacturing,multi-stage,yarn-dyed textile production,textile,textile industry
Mathematical optimization,Job shop scheduling,Fair-share scheduling,Computer science,Flow shop scheduling,Open-shop scheduling,Two-level scheduling,Rate-monotonic scheduling,Earliest deadline first scheduling,Dynamic priority scheduling
Journal
Volume
Issue
ISSN
36
10
Expert Systems With Applications
Citations 
PageRank 
References 
8
0.55
8
Authors
4
Name
Order
Citations
PageRank
Hsi-Mei Hsu119932.69
Yai Hsiung280.89
Ying-Zhi Chen380.55
Muh-Cherng Wu422716.58