Integrated Process Planning and Scheduling Based on Genetic Algorithms

Abstract:

Process planning and scheduling are two important manufacturing activities in the manufacturing system. In this paper, an improved genetic algorithm(GA) has been developed to facilitate the integration and optimization of process planning and scheduling. To improve the optimization performance, an efficient genetic representation has been developed. Selection, crossover, and mutation operators have been described. Simulation studies have been established to evaluate the performance of the algorithm. The results show that the algorithm is a promising and effective method for the integration of process planning and scheduling(IPPS).

• Periodical: Advanced Materials Research (Volumes 291-294)
• Pages: 331-334
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.291-294.331
• Online since: July 2011
• Authors: Jin Feng Wang, Shi Jie Li, Shun Cheng Fan
• Keywords: Crossover, Genetic Algorithm (GA), Mutation, Process Planning and Scheduling

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