Integrated Scheduling of Multi-Objective Job Shops and Material Handling Robots with Reinforcement Learning Guided Meta-Heuristics

Zhangying Xu, Qi Jia, Kaizhou Gao (), Yaping Fu (), Li Yin and Qiangqiang Sun
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Zhangying Xu: Macau Institute of Systems Engineering, Macau University of Science and Technology, Macao 999078, China
Qi Jia: Macau Institute of Systems Engineering, Macau University of Science and Technology, Macao 999078, China
Kaizhou Gao: Macau Institute of Systems Engineering, Macau University of Science and Technology, Macao 999078, China
Yaping Fu: School of Business, Qingdao University, Qingdao 266071, China
Li Yin: Macau Institute of Systems Engineering, Macau University of Science and Technology, Macao 999078, China
Qiangqiang Sun: School of Information Engineering, Shandong University of Aeronautics, Binzhou 256603, China

Mathematics, 2024, vol. 13, issue 1, 1-28

Abstract: This study investigates the integrated multi-objective scheduling problems of job shops and material handling robots (MHR) with minimising the maximum completion time (makespan), earliness or tardiness, and total energy consumption. The collaborative scheduling of MHR and machines can enhance efficiency and reduce costs. First, a mathematical model is constructed to articulate the concerned problems. Second, three meta-heuristics, i.e., genetic algorithm (GA), differential evolution, and harmony search, are employed, and their variants with seven local search operators are devised to enhance solution quality. Then, reinforcement learning algorithms, i.e., Q-learning and state–action–reward–state–action (SARSA), are utilised to select suitable local search operators during iterations. Three reward setting strategies are designed for reinforcement learning algorithms. Finally, the proposed algorithms are examined by solving 82 benchmark instances. Based on the solutions and their analysis, we conclude that the proposed GA integrating SARSA with the first reward setting strategy is the most competitive one among 27 compared algorithms.

Keywords: job shop scheduling problem (JSP); material handling robots; meta-heuristics; local search (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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