文献类型：期刊文献

英文题名：Robust Order Scheduling in the Discrete Manufacturing Industry: A Multiobjective Optimization Approach

作者：Du, Wei[1];Tang, Yang[1];Leung, Sunney Yung Sun[2];Tong, Le[2];Vasilakos, Athanasios V.[3];Qian, Feng[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Hong Kong Polytech Univ, Inst Text & Clothing, Hong Kong, Hong Kong, Peoples R China;[3]Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, S-97187 Lulea, Sweden

年份：2018

卷号：14

期号：1

起止页码：253

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：;EI(收录号：20180404666759);WOS:【SCI-EXPANDED(收录号:WOS:000422661900025)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61422303 and 61673176, in part by China Postdoctoral Science Foundation under Grant 2016M601525, in part by Shanghai Sailing Program, and in part by the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017.

语种：英文

外文关键词：Order scheduling; preproduction events; robust multiobjective evolutionary algorithms (MOEAs); robust multiobjective optimization

摘要：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.