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- Title
An improved genetic algorithm for integrated process planning and scheduling.
- Authors
Lihong, Qiao; Shengping, Lv
- Abstract
Process planning and scheduling are two of the most important functions involved in manufacturing process and they are actually interrelated; integration of the two is essential to improve the flexibility of scheduling and achieve a global improvement for the performance of a manufacturing system. In order to facilitate the optimization of process planning and scheduling simultaneously, a mathematical model for the integrated process planning and scheduling (IPPS) is established, and an improved genetic algorithm (IGA) is proposed for the problem. For the performance improvement of the algorithm, new initial selection method for process plans, new genetic representations for the scheduling plan combined with process plans and genetic operator method are developed. To verify the feasibility and performance of the proposed approach, experimental studies are conducted and comparisons are made between this approach and others with the makespan and mean flow time performance measures. The results show that the proposed approach on IPPS has achieved significant improvement in minimizing makespan and obtained good results for the mean flow time performance measure with high efficiency.
- Subjects
PRODUCTION planning; GENETIC algorithms; PRODUCTION scheduling; MANUFACTURING processes; MATHEMATICAL models; FEASIBILITY studies; MATHEMATICAL functions
- Publication
International Journal of Advanced Manufacturing Technology, 2012, Vol 58, Issue 5-8, p727
- ISSN
0268-3768
- Publication type
Article
- DOI
10.1007/s00170-011-3409-0