Robust Order Scheduling in the Discrete Manufacturing Industry: A Multiobjective Optimization Approach
Robust Order Scheduling in the Discrete Manufacturing Industry: A Multiobjective Optimization Approach
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DOI：
10.1109/tii.2017.2664080
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发表时间：
2017-02
影响因子：
12.3
通讯作者：
Wei Du;Yang Tang;S. Leung;Le Tong;A. Vasilakos;F. Qian
中科院分区：
文献类型：
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作者：
Wei Du;Yang Tang;S. Leung;Le Tong;A. Vasilakos;F. Qian
订单调度是离散制造业中的一个重要问题。本文以服装行业为例，讨论了服装行业的鲁棒订单调度问题。在时装行业，订单调度的重点是将生产订单分配到适当的生产线。实际上，在新订单投入生产之前，需要完成一系列称为预生产事件的活动。此外，在真实的生产过程中，由于各种不确定性，每个订单的日生产量并不总是如预期的那样。在本文中，考虑到预生产事件和不确定性的日常生产量，鲁棒订单调度问题在时装业的援助，一个多目标的进化算法称为非支配排序自适应差分进化（NSJADE）。实验结果表明，它是至关重要的，考虑在时装业的订单调度问题的预生产事件。同时揭示了日生产量不确定性的存在对订单调度的影响。
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.