High-Dimensional Robust Multi-Objective Optimization for Order Scheduling: A Decision Variable Classification Approach
High-Dimensional Robust Multi-Objective Optimization for Order Scheduling: A Decision Variable Classification Approach
复制标题
订单调度的高维鲁棒多目标优化：决策变量分类方法
DOI：
10.1109/tii.2018.2836189
复制
发表时间：
2019-01-01
影响因子：
12.3
通讯作者：
Jin, Yaochu
中科院分区：
文献类型：
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作者：
Du, Wei;Zhong, Weimin;Jin, Yaochu
研究了高维鲁棒订单排序问题。提出了一种基于决策变量分类的约束非支配排序差分进化多目标进化算法，用于求解鲁棒订货计划问题。根据决策变量对候选解鲁棒性的贡献，将决策变量分为强鲁棒性相关变量和弱鲁棒性相关变量。实验结果表明，通过分析决策变量的性质，对高维鲁棒优化问题进行分解，可以大大提高鲁棒进化优化的性能。同时也揭示了日生产量的不确定性对订单调度的影响。鲁棒订单调度能够提供更多的订单提前/拖期信息，提高了生产的灵活性。
This paper tackles the high-dimensional robust order scheduling problem. A multi-objective evolutionary algorithm called constrained nondominated sorting differential evolution based on decision variable classification is developed to search for robust order schedules. The decision variables are classified into highly and weakly robustness-related variables according to their contributions to the robustness of candidate solutions. The experimental results reveal that the performance of robust evolutionary optimization can be greatly improved via analyzing the properties of decision variables and then decomposing the high-dimensional robust optimization problem. It is also unveiled that the order scheduling is greatly affected by the uncertain daily production quantities. The robust order schedules are able to provide more information on earliness/tardiness of the orders, which enhances the flexibility of the production.