A Novel Production Scheduling Approach Based on Improved Hybrid Genetic Algorithm

Subjects: Engineering and technical science >> Engineering General Technology submitted time 2024-05-10

Lili Dai He Lu Dezheng Hua Xinhua Liu Hongming Chen Adam Glowacz Grzegorz Królczyk Z Li

Abstract： Due to the complexity of the production shop in discrete manufacturing industry, traditional genetic algorithm (GA) cannot solve the production scheduling problem well. In order to enhance the GA-based method to solve the production scheduling problem, the simulated annealing algorithm (SAA) is used to develop an improved hybrid genetic algorithm. Firstly, the crossover probability and mutation probability of the genetic operation are adjusted, and the elite replacement operation is adopted for simulated annealing operator. Then, a mutation method is used for the comparison and replacement of the genetic operations to obtain the optimal value of the current state. Lastly, the proposed hybrid genetic algorithm is compared with several scheduling algorithms, and the superiority and efficiency of the proposed method are verified in solving the production scheduling.

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