Study On Multi-objective Flow Shop Optimal Scheduling Problem Considering Worker Load

Flow shop refers to the production mode formed by the arrangement of multiple production lines in the form of flow shop,which generally exists in cable,household appliances,automobile manufacturing,steel and other industries.Flow Shop Scheduling Problem(Flow Shop Scheduling Problem)with the people for engineering approach in the management of the workshop application,as well as the effective implementation of the enterprise for the occupational health and safety management system,considering the influence of the workers load of Flow Shop Scheduling decision,and explore establishing corresponding optimization Scheduling model and its solving method,has the important research value and significance,is also the good expansibility study of classic Flow Shop Scheduling Problem.Firstly,this paper aiming at flow shop scheduling workers work load imbalance,definition,with the consideration of workers to load the scope and connotation of flow shop scheduling problem,considering the customer's requirements,technical requirements,the allocation of resources and people died as a result of engineering and so on many factors,to quantify the energy consumption of flow shop workers efficiency and the effect of load balance based on the system efficiency priority and workers,determined to minimize all artifacts of delay time and minimize the workers work distribution load standard deviation as the decision goal,considering the technical constraints,constraints(processing),customer preferences(delivery),team resource constraints,worker fatigue constraints,etc.,A dual objective optimal scheduling model is constructed.Secondly,Aiming at the problem of selection and design of algorithm for solving the model,this paper expounds the advantages of fast non-dominant sequencing genetic algorithm(NSGA-?)with elite strategy,and gives the rationality and applicability of selecting NSGA-? algorithm through literature analysis.The NSGA-? algorithm based on bichromosome coding was designed in combination with the description and decision-making process of the flow-shop optimal scheduling problem with worker load in mind.The algorithm has been reconstructed and implemented in five aspects including the design of bichromosome coding mode,the generation of initial population,the setting of fitness function,the calculation of non-dominant ordering and crowding degree,and the evolutionary operation,and finally the pareto optimal solution set of the model has been obtained.Finally,the application and solution of the model are given through the example of characteristic calculation in thus paper.Two NSGA-?-SPT and NSGA-?-EDD algorithms embedded with heuristic rules were introduced as comparison algorithms to analyze the performance of the double-chromosome NSGA-? algorithm.The number N of Pareto solutions,the error ratio of Pareto frontier solutions,the span of Pareto frontier and the operation time of the algorithm were used as the performance evaluation indexes.Comparative analysis shows that the model and algorithm are effective.The bichromosome NSGA-? algorithm has a good solution advantage.As the number of artifacts increased,the performance of the model and its bichromosome NSGA-? algorithm became more stable.