New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system - Xiaoxiao Wei; Jiafan Sun; Haojin Jiao (Scientific Reports)
Abstract The equipment layout design of a reconfigurable manufacturing system can be determined by a variety of algorithms. The complexity of the problem increases with the increase of dimension, and it is a typical NP hard problem. In this paper, a new improved hybrid genetic algorithm is proposed to solve this problem. Firstly, the chaos genetic algorithm based on improved Tent map is used to enhance the quality and diversity of the initial population. In order to reduce the complexity of the problem, this paper applies the association rule theory to mine the dominant blocks in the population and to combine the artificial chromosomes. After matched crossover and mutation operations on the layout encoding string, a small adaptive chaotic perturbation is applied to the genetically optimized optimal solution. Finally, through comparison of experimental results and algorithms, it can be concluded that the proposed method is superior to traditional methods in terms of both accuracy and efficiency.