Article ID: | iaor20115556 |
Volume: | 126 |
Issue: | 2 |
Start Page Number: | 289 |
End Page Number: | 298 |
Publication Date: | Aug 2010 |
Journal: | International Journal of Production Economics |
Authors: | Li Xinyu, Shao Xinyu, Gao Liang, Qian Weirong |
Keywords: | scheduling, planning, heuristics: genetic algorithms, heuristics: local search |
Process planning and scheduling are two of the most important functions in the manufacturing system. Traditionally, process planning and scheduling were regarded as separate tasks performed sequentially, where scheduling was implemented after process plans had been generated. However, their functions are usually complementary. If the two systems can be integrated more tightly, greater performance and higher productivity of manufacturing system can be achieved. In this paper, a new hybrid algorithm (HA) based approach has been developed to facilitate the integration and optimization of these two systems. To improve the optimization performance of the approach, an efficient genetic representation, operator and local search strategy have been developed. Experimental studies have been used to test the performance of the proposed approach and to make comparisons between this approach and some previous works. The results show that the research on integrated process planning and scheduling (IPPS) is necessary and the proposed approach is a promising and very effective method on the research of IPPS.