Hierarchical multistrategy genetic algorithm for integrated process planning and scheduling
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Hierarchical multistrategy genetic algorithm for integrated process planning and scheduling Xu Zhang1 · Zhixue Liao2 · Lichao Ma3 · Jin Yao3 Received: 15 January 2020 / Accepted: 23 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract To adapt to the flexibility characteristics of modern manufacturing enterprises and the dynamics of manufacturing subsystems, promote collaboration in manufacturing functions, and allocate production resources in a reasonable manner, a mathematical model of integrated process planning and scheduling (IPPS) problems was developed to optimize the global performance of manufacturing systems. To solve IPPS problems, a hierarchical multistrategy genetic algorithm was developed. To address the multidimensional flexibility of IPPS problems, a chromosome coding method was designed to include a scheduling layer, a process layer, a machine layer, and a logic layer. Multiple crossover operators and mutation operators with polytypic global or local optimization strategies were used during the genetic operation stage to expand the algorithm’s search dimension and maintain the population’s diversity, thereby addressing the problems of population evolution stagnation and premature convergence. The effectiveness of the algorithm was verified by benchmark testing in the example simulation process. The test data show that if the makespan is taken as the optimization target, the proposed genetic algorithm performs better in solving IPPS problems with high complexity. The use of multistrategy genetic operators and logic layer coding makes a significant contribution to the improved performance of the algorithm reported in this paper. Keywords Process planning · Jopshop scheduling · Multistrategy · Genetic algorithm
Introduction To meet increasingly diversified market requirements, many manufacturing enterprises have adopted a high-mix lowvolume production mode. Flexible manufacturing system layouts have become the mainstream trend in manufacturing enterprises. Studies related to flexible manufacturing systems focus on process planning and job shop scheduling. The technology behind computer-aided process planning is becoming more and more mature, which shortens the cycle of process design and increases the flexibility of product processes. The flexibility of process planning and production equipment greatly enhances the flexibility of enterprise pro-
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Jin Yao [email protected]
1
Business School, Sichuan University, Chengdu 610064, China
2
School of Business Administration, Southwestern University of Finance and Economics, 555, Liutai Avenue, Wenjiang District, Chengdu 611130, China
3
School of Mechanical Engineering, Sichuan University, Chengdu 610064, China
duction but increases the difficulty of job shop scheduling. As the link between product design and product manufacturing, product process planning determines the processing method, processing sequence, processing parameters, machine and equipment resources, processing time, and other conditions (Sugimur
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