Optimization of Earliness and Tardiness Scheduling in Job Shop with Uncertain Processing Times Using Grey Numbers
With respect to the job shop scheduling problem with uncertain processing times,the due date windows of each job is considered,aiming to minimize the earliness/tardiness cost of chemical components and the idle cost of machines.Use basic genetic algorithm and hybrid genetic algorithm respectively for sol-ving,and compare the solution quality of the two algorithms.Establish scheduling models for uncertain pro-cessing times using grey theory and fuzzy numbers,and analyze the optimization degree and stability of the two models.The results show that compared with basic genetic algorithms,hybrid genetic algorithms that introduce local search based on specified neighborhood structures have better convergence ability;Compared with the fuzzy number method,using grey theory can better describe uncertain processing times,and it also has better adaptability and stability in the solving process.
uncertain processing timedue date windowsearliness/tardinessgrey theoryhybrid genetic algorithmlocal search
NETL
NSTL
万方数据
维普
