文献类型：期刊文献

英文题名：Robust order scheduling in the fashion industry: A multi-objective 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] Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China; [2] Institute of Textile and Clothing, Hong Kong Polytechnic University, Hong Kong, Hong Kong; [3] Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Lulea, 97187, Sweden

年份：2017

外文期刊名：arXiv

收录：EI(收录号：20200338824)

语种：英文

外文关键词：Evolutionary algorithms - Scheduling

摘要：—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 pre-production 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 research, by considering the pre-production events and the uncertainties in the daily production quantity, robust order scheduling problems in the fashion industry are investigated with the aid of a multi-objective evolutionary algorithm (MOEA) called nondominated sorting adaptive differential evolution (NSJADE). The experimental results illustrate that it is of paramount importance to consider pre-production 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. Copyright ? 2017, The Authors. All rights reserved.