Considering The Resource Constraints And Preventive Maintenance Of Hybrid Flow Shop Scheduling Problem Is Studied

This paper based on sichuan youth foundation project “Round about productionprocess oriented multi-objective production planning research”. Hybrid flow shopscheduling problem is the promotion of the flow shop and parallel shop which are thetwo kinds of classic scheduling problems, while in contrast, HFSS problem requiresmore than two parallel machines at least in one stage throughout the whole process,which is more complex NP complete problem. Two problems should be resolved atone time: the machining sequence of each workpiece and the distribution of themachines in each processing stage.For the scarce resources constraints of hybrid flow shop scheduling problem, theinfluence of resource constrains on the makespan was considered into object functionto build mathematical model, then the goals of maximum utilization of scarceresources and minimum makespan were achieved. Because the genetic algorithm hasthe drawbacks of premature convergence during the solution process, the improvedgenetic algorithm which using NEH heuristic algorithm to generate initial populationwas proposed. Simulation research shows that the improved genetic algorithm is moreeffective than the simple genetic algorithm in solving scarce resources constraints forhybrid flow shop scheduling problem.In the production process, because regularly preventive maintenance is inevitable,the influence that preventive maintenance makes on production scheduling should beconsidered. Based on resource constrains on scheduling model, the influence ofpreventive maintenance and scarce resource constrains on the initial processing timewere considered into object function to build optimal scheduling model. These modelscould meet the optimization allocation of limited resources and regular equipmentpreventive maintenance, meanwhile, making the maximum equipment utilization andshortest production cycle. In order to solve the complicated constraints schedulingproblem, new heuristic rules were proposed, combining with genetic algorithm forsolving scheduling model.A case indicates that the improved algorithm can get better scheduling option.At last, two types of scheduling models in this paper were compared withtraditional scheduling models by calculating every scheduling index with awind-power blade factory actual workshop data. The results show that the proposedscheduling models are more effective in solving scarce resources constraints andpreventive maintenance of hybrid flow shop scheduling problem, achieving thepurpose of higher resource utilization and shorter production cycle.