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.

中文翻译：

---

订单调度的高维稳健多目标优化：决策变量分类方法

本文解决了高维鲁棒订单调度问题。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约束的多目标进化算法来搜索鲁棒的订单计划。根据决策变量对候选解决方案的鲁棒性的贡献，将其分为与鲁棒性相关的高度变量和与之无关的变量。实验结果表明，通过分析决策变量的性质，然后分解高维鲁棒优化问题，可以极大地提高鲁棒进化优化的性能。还揭露了不确定的每日生产量极大地影响了订单计划。