A Genetic Algorithm for Integration of Process Planning and Scheduling Problem

  • Authors:

  • Xinyu Li;Liang Gao;Guohui Zhang;Chaoyong Zhang;Xinyu Shao

  • Affiliations:

  • The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China

  • Venue:
  • ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
  • Year:
  • 2008

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Abstract

Traditionally, process planning and scheduling for parts are carried out in a sequential way, where scheduling is done after process plans have been generated. Considering the two functions are usually complementary, there is a great potential to integrate them more tightly so that greater performance and higher productivity of a manufacturing system can be achieved. In this paper, a genetic algorithm-based approach has been developed to facilitate the integration and optimization of these two functions. To improve the optimized performance of the genetic algorithm-based approach, efficient genetic representations and operator schemes have been developed. Experiment studies have been conducted. The experimental results show that the proposed approach is a promising and very effective method for the integration of process planning and scheduling.