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A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing

A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing

Ehsan Ardjmand, William A. Young II, Iman Ghalehkhondabi, Gary R. Weckman
Copyright: © 2021 |Volume: 12 |Issue: 4 |Pages: 19
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781799861232|DOI: 10.4018/IJORIS.20211001.oa4
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MLA

Ardjmand, Ehsan, et al. "A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing." IJORIS vol.12, no.4 2021: pp.1-19. http://doi.org/10.4018/IJORIS.20211001.oa4

APA

Ardjmand, E., Young II, W. A., Ghalehkhondabi, I., & Weckman, G. R. (2021). A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing. International Journal of Operations Research and Information Systems (IJORIS), 12(4), 1-19. http://doi.org/10.4018/IJORIS.20211001.oa4

Chicago

Ardjmand, Ehsan, et al. "A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing," International Journal of Operations Research and Information Systems (IJORIS) 12, no.4: 1-19. http://doi.org/10.4018/IJORIS.20211001.oa4

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Abstract

The manufacturing environment for apparel is subject to a variety of constraints, stochasticity, and unforeseen events. In order to create an accurate scheduling-system for this environment, these complexities must be considered. This article presents the development and the application of a scheduling and rescheduling decision support system for an apparel manufacturer. Furthermore, the results of applying the proposed system are presented and discussed. The scheduling and rescheduling decision support system presented in this article takes advantage of a variable neighborhood search and Monte Carlo simulation in order to minimize tardiness in the presence of different release times, sequence-based setup times, blocking, and resource constraints. The results show that the quality of the schedules generated by the proposed scheduling and rescheduling decision support system is superior to the current firm’s scheduling practice, which is based on an earliest due date heuristic. Moreover, the percentage of the realized schedule and overall equipment effectiveness were improved.