Dynamic Scheduling Optimization of Job Shop Based on OCTPN and Hybrid Genetic Algorithms
Combining colored Petri net with object-oriented technology,a new object-oriented colored timed Petri net (OCTPN) method was proposed and the scheduling model of a dual-resource constrained job shop was built.The model has good reusability comparing with the model built by process-oriented technology.A hybrid genetic algorithm based on Pareto was proposed and applied to flexible job shop scheduling problem (FJSP) with bi-objective,where the make-span and the production cost were concerned.The algorithm uses the niche technology and many kinds of crossover operations to get the optimum solutions,most importantly,it can generate new scheduling plan rapidly after the disturbance occurred.The simulation experiment is carded out to illustrate that the proposed method can solve bi-objective job shop scheduling problem effectively.
Petri net Hybrid genetic algorithm Dynamic scheduling Bi-objective
Xiaoxia Liu Bingyi Yan Daizhong Bai
Henan University of Technology,Zhengzhou,450007,China Heze Power Company Limited,Heze,274032,China
国际会议
沈阳
英文
1221-1224
2012-09-26（万方平台首次上网日期，不代表论文的发表时间）