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A Review on Intelligent Scheduling and Optimization for Flexible Job Shop

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Abstract

Flexible job shop scheduling problem is a NP-hard combinatorial optimization problem, which has significant applications in the field of workshop scheduling and intelligent manufacturing. Due to its complexity and significance, lots of attention have been paid to tackle this problem. This paper reviews some of the researches on this problem, by presenting and classifying the different criteria, constraints, and solution approaches. The existing solution methods for the flexible job shop scheduling problem in this literature are classified into exact algorithms, heuristics, and meta-heuristics, which are thoroughly reviewed. Particularly, the paper highlights the flexible job shop scheduling problem in the context of dynamic events and preventive maintenance. These dynamic events, such as machine breakdowns and unexpected changes in job requirements, present additional challenges to the scheduling problem. Furthermore, this paper analyzes the development trends in the manufacturing industry and summarizes detailed future research opportunities for the flexible job shop scheduling problem.

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Authors and Affiliations

  1. Department of Automatic Control, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Bin Jiang, Yajie Ma, Yuying Huang & Li Guan

  2. AVIC Nanjing Engineering Institute of Aircraft System, Nanjing, 210016, China

    Lijun Chen

  3. Department of Engineering and Technology, AVIC Nanjing Engineering Institute of Aircraft System, Nanjing, 210016, China

    Binda Huang

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  1. Bin Jiang
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Correspondence to Bin Jiang.

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The authors declare that there is no competing financial interest or personal relationship that could have appeared to influence the work reported in this paper. Bin Jiang currently serves as a Senior Editor for International Journal of Control, Automation, and Systems.

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This work was supported by the National Key Research and Development Program of China (No. 2021YFB3301300).

Bin Jiang received his Ph.D. degree in automatic control from Northeastern University, Shenyang, China, in 1995. He had ever been a Post-Doctoral Fellow, a Research Fellow, an Invited Professor, and a Visiting Professor in Singapore, France, USA, and Canada, respectively. He is currently a Chair Professor of the Cheung Kong Scholar Program with the Ministry of Education and the Vice President of the Nanjing University of Aeronautics and Astronautics, Nanjing, China. He has authored eight books and over 100 referred international journal articles. His current research interests include intelligent fault diagnosis and fault tolerant control and their applications to helicopters, satellites, and high-speed trains. He is a fellow of the Chinese Association of Automation (CAA). He was a recipient of the Second-Class Prize of National Natural Science Award of China. He currently serves as a Senior Editor for International Journal of Control, Automation, and Systems, an Associate Editor or an Editorial Board Member for a number of journals, such as the IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Industrial Informatics. He is also a Chair of Control Systems Chapter in IEEE Nanjing Section, and a member of the IFAC Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. He is an IEEE fellow.

Yajie Ma received his B.S. degree in automation from the Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China, in 2008, an M.S. degree in detection technology and automatic equipment from Hohai University, Nanjing, in 2011, and a Ph.D. degree in controle theory and control engineering from the NUAA, in 2015. From 2015 to 2016, he was a Postdoctoral Fellow with the Research Center in Computer Science, Signal Processing and Automatic Control (CRIStALCNRS UMR 9189), Lille, France. He is currently a Professor with the College of Automation Engineering, NUAA. His research interests include adaptive fault diagnosis and fault-tolerant control and their applications. He is an IEEE member.

Lijun Chen is Deputy General Manager, Chief Engineer AVIC Nanjing Engineering Institute of Aircraft Systems Graduated from Nanjing University of Aeronautics and Astronautics in 2006. Chen is now the deputy manager and chief engineer of AVIC Nanjing Engineering Institute of Aircraft Systems, a director of Integrated Electromechanical System Division. He used to be a director of Hydraulic & Actuation System Division, Technology & Information Department and Scientific & Technological Development Department. Chen has been in charge of civil aircraft hydraulic system technology research, the research work of advanced EHA, EMA, the research work of front wheel turning system and other key projects, and contributed to the building of R&D system of NEIAS. Chen won three personal merits of the Aviation Industry Group, one third prize of National Defense Science and Technology Progress Award, three second prizes and one third prize of Group Science and Technology Progress Award, as well as three invention patents and four core papers. As a black-belt owner of DFSS and a registered system engineer of INCOSE Association, he values practice of systematic engineering methods and lean thinking in actual research. He was selected as a candidate of 333 Talent Project of Jiangsu Province.

Binda Huang recieived his B.S. degree in design and manufacture of machinery and automation from Nanchang Hangkong University (NCHU), Nanchang, China, in 2008, an M.S. degree in aerospace manufacturing engineering from the NCHU, in 2011, and a Ph.D. degree in aerospace manufacturing engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, in 2016. He is currently a senior engineer with the Department of Engineering and Technology, AVIC Nanjing Engineering Institute of Aircraft System. His research interests include digital twin and smart manufacturing.

Yuying Huang received her B.E. degree from the School of Electrical Engineering and Automation, Hefei University of Technology, China in 2021. She is currently a postgraduate student in College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. Her research interests include flexible job shop scheduling and swarm intelligence algorithm.

Li Guan received his B.E. degree from the School of Electrical Engineering and Automation, Soochow University in 2022. He is currently a postgraduate student in College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. His research interests include flexible job shop scheduling, reliability and maintainability engineering, and multiobjective evolutionary algorithm.

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Jiang, B., Ma, Y., Chen, L. et al. A Review on Intelligent Scheduling and Optimization for Flexible Job Shop. Int. J. Control Autom. Syst. 21, 3127–3150 (2023). https://doi.org/10.1007/s12555-023-0578-1

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