A genetic algorithm for integration of process planning and scheduling in a job shop

  • Authors:
  • Byung Joo Park;Hyung Rim Choi

  • Affiliations:
  • Department of Management Information System, Dong-A University, Busan, Korea;Department of Management Information System, Dong-A University, Busan, Korea

  • Venue:
  • AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
  • Year:
  • 2006

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Abstract

This study focused on the integration problem of process planning and scheduling in a job shop environment. In an effort to integrate process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we have designed a GA (Genetic Algorithm)-based scheduling method. The performance of this newly suggested GA-based method has been evaluated by comparing integrated scheduling with separated scheduling in a real company that has alternative process plans. Also, a couple of benchmark cases have been tested for performance evaluation.