Mathematical modeling and evolutionary algorithm-based approach for integrated process planning and scheduling

Authors:
Xinyu Li;Liang Gao;Xinyu Shao;Chaoyong Zhang;Cuiyu Wang
Affiliations:
The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
Venue:
Computers and Operations Research
Year:
2010

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Abstract

Traditionally, process planning and scheduling were performed sequentially, where scheduling was implemented after process plans had been generated. Considering their complementarity, it is necessary to integrate these two functions more tightly to improve the performance of a manufacturing system greatly. In this paper, a mathematical model of integrated process planning and scheduling has been formulated. And, an evolutionary algorithm-based approach has been developed to facilitate the integration and optimization of these two functions. To improve the optimized performance of the approach, efficient genetic representation and operator schemes have been developed. To verify the feasibility and performance of the proposed approach, experimental studies have been conducted and comparisons have been made between this approach and some previous works. The experimental results show that the integrated process planning and scheduling is necessary and the proposed approach has achieved significant improvement.