Research on Scheduling of Dual-Resource Constrained Job Shop
In this paper, a dual-resource constrained job shop scheduling problem was studied by designing a scheduling method based on Genetic Algorithm (GA) and Simulated Annealing (SA). The combination of GA and SA has higher degree of convergence precision by utilizing GA excellent global search ability and SA efficient to avoid getting into part minimum. The operation -based encoding and an active schedule decoding method were employed, and several kinds of crossover operations were adopted in order to promote solution diversity. This hybrid genetic algorithm reasonably assigns the resources of machines and workers to jobs and achieves optimum on some performance. Compared with the solutions suggested by other researchers, the developed algorithm can search better solution on make-span and mean flow time, and can receive higher machine utilizat ion and worker ut ilization. In conclusion, the algorithm proposed in this paper is available and efficient.
job shop scheduling dual resources hybrid genetic algorithm
Liu Xiaoxia Cai Gangyi Cui Jingwei
School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou, P.R.China, School of Mechanical Engineering, University of Shenyang, Shenyang, P.R.China, 110044
国际会议
4th International Conference on Productinnovation Management(第四届产品创新管理国际会议)
武汉
英文
1742-1748
2009-08-22（万方平台首次上网日期，不代表论文的发表时间）