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A Q-learning-based Automatic Heuristic Design Approach for Seru Scheduling

Seru production is a new mode of production with the advantages of quick response, high flexibility and high efficiency. It is well suited to the market that fluctuates frequently. The seru scheduling is an important issue for seru production system configuration problem because it reflects the management and control principle of seru production systems, which called just-in-time operation system. This paper studies a seru scheduling problem, which can be described as how to determine the sequence of serus in limited space for multiple orders considering worker overlapping. The objective is to minimize the maximum completion time. A Q-learning-based genetic programming algorithm is proposed to solve the above problem. Experimental results show the effectiveness of the proposed algorithm.