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ABSTRACT
This paper addresses the no-wait job shop scheduling problem with due date and subcontracting cost constraints. For the no-wait job shop problem, it does not allow for waiting or interruption between any two consecutive operations of the same job. Considering the deadline and controllable processing time requirements in the real world, due date and subcontracting cost constraints are integrated into the problem as a new extension. The problem has two objectives which are associated with makespan and subcontracting cost. The extended problem focuses on a special case that some jobs cannot satisfy their deadlines no matter how they are scheduled. To satisfy the deadlines, a subcontracting strategy, i.e. buying semi-finished products for processing, is put forward. Two mathematical models are proposed. One is an integrated MILP (MILP-IS), and the other is a rolling time line MILP (MILP-RTL). According to the idea of rolling time line, an artificial bee colony algorithm based on rolling time line (RTL-ABC) is developed. Comprehensive computational analysis is carried out. For small size problems, the optimal solutions are obtained by using these two mathematical models. For large size problems, RTL-ABC is able to find good-quality solutions in a reasonable time and improves the best-found solutions.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Jinsheng Gao
Jinsheng Gao received the MS degree from Beijing Jiaotong University, Beiing, China, in 2017. Now, he is a PhD candidate with the School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China. His current research interests include operations research, intelligent heuristic and artificial intelligence.
Xiaomin Zhu
Xiaomin Zhu got her PhD from the Technical University of Crete in Greece in 2004, and received her BS and MS degrees from Tianjin University, Tianjin, China, in 1985 and in 1988, respectively. She is presently a professor at Beijing Jiaotong University. Her research interests include artificial intelligence, system evaluation and optimiation, fuzzy control, and operations research. She has been a PI for over 50 research projects, and has published 80 papers and 15 books in these fields.
Kaiyuan Bai
Kaiyuan Bai received the BS degree from Lanzhou University of Technology, Lanzhou, Gansu, China. Now, he is a PhD candidate with the School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China. His current research interests include fuzzy group decision making, expert system, and artificial intelligence
Runtong Zhang
Runtong Zhang got his PhD in Production Engineering and Management from Technical University of Crete in Greece in 1996, and his BS in Computer Science and Automation from the Dalian Maritime University in China in 1985, respectively. He is presently a professor and head of the Department of Information Management at Beijing Jiaotong University, China. He was also with the Swedish Institute of Computer Science as a senior researcher, and the Port of Tianjin Authority as an engineer. His current research interests include artificial intelligence, big data, health-care management, and operations research. He has published over 300 papers in referenced journals and conferences, and 40 books. He has been a PI for over 100 research projects and is a holder of 9 patents. He has been Senior Member, IEEE and a general chair or co-chair for over 10 IEEE sponsored international conferences.