Robust single machine scheduling problem with uncertain job due dates for industrial mass production

作     者：YUE Fan SONG Shiji JIA Peng WU Guangping ZHAO Han YUE Fan;SONG Shiji;JIA Peng;WU Guangping;ZHAO Han

作者机构：Department of AutomationTsinghua UniversityBeijing 100084China Research Institute of Systems EngineeringBeijing 100072China Jiuquan Satellite Launch CentreJiuquan 735000China Department of Basic ScienceArmy Logistics AcademyChongqing 401311China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2020年第31卷第2期

页      面：350-358页

核心收录：

学科分类：120202[管理学-企业管理（含：财务管理、市场营销、人力资源管理）] 12[管理学] 1202[管理学-工商管理] 

基　　金：supported by the National Natural Science Foundation of China(61503211 U1660202) 

主　　题：robust optimization single machine scheduling maximum tardiness uncertain due date 

摘      要：The single machine scheduling problem which involves uncertain job due dates is one of the most important issues in the real make-to-order environment. To deal with the uncertainty, this paper establishes a robust optimization model by minimizing the maximum tardiness in the worst case scenario over all jobs. Unlike the traditional stochastic programming model which requires exact distributions, our model only needs the information of due date intervals. The worst case scenario for a given sequence that belongs to a set containing only n scenarios is proved, where n is the number of jobs. Then, the model is simplified and reformulated as an equivalent mixed 0-1 integer linear programming(MILP) problem. To solve the MILP problems efficiently, a heuristic approach is proposed based on a robust dominance rule. The experimental results show that the proposed method has the advantages of robustness and high calculating efficiency, and it is feasible for large-scale problems.