Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77450
Title: Robust order scheduling in the discrete manufacturing industry : a multiobjective optimization approach
Authors: Du, W
Tang, Y
Leung, SYS 
Tong, L 
Vasilakos, AV
Qian, F
Keywords: Order scheduling
Preproduction events
Robust multiobjective evolutionary algorithms (MOEAs)
Robust multiobjective optimization
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial informatics, 2018, v. 14, no. 1, 7842622, p. 253-264 How to cite?
Journal: IEEE transactions on industrial informatics 
Abstract: Order scheduling is of vital importance in discrete manufacturing industries. This paper takes fashion industry as an example and discusses the robust order scheduling problem in the fashion industry. In the fashion industry, order scheduling focuses on the assignment of production orders to appropriate production lines. In reality, before a new order can be put into production, a series of activities known as preproduction events need to be completed. In addition, in real production process, owing to various uncertainties, the daily production quantity of each order is not always as expected. In this paper, by considering the preproduction events and the uncertainties in the daily production quantity, robust order scheduling problems in the fashion industry are investigated with the aid of a multiobjective evolutionary algorithm called nondominated sorting adaptive differential evolution (NSJADE). The experimental results illustrate that it is of paramount importance to consider preproduction events in order scheduling problems in the fashion industry. We also unveil that the existence of the uncertainties in the daily production quantity heavily affects the order scheduling.
URI: http://hdl.handle.net/10397/77450
ISSN: 1551-3203
EISSN: 1941-0050
DOI: 10.1109/TII.2017.2664080
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