Research On Application Of Improved Genetic Algorithm On Shop Scheduling Problem

Production scheduling is the core competencies of production management whichwill affect the plan implementation and rational allocation of limited resources. Manyenterprises still rely on experienced planner arrange the scheduling manually until now,but the manual scheduling becomes very inefficient, even impossible to allocate theresources in the optimal way under the situation of personalization, diversification,small-volume orders and dynamically changing market environment. Research thescheduling methods and develop feasible scheduling information system based onbusiness model and product process of the enterprise will improve operation efficiencyand enhance the competitiveness of enterprises.Taking Schaffner EMC (Shanghai) Co., Ltd. as the research target, this paper isaimed to find out an optimal scheduling method to shorten production lead time thusimproving resource utilization and enhancing production efficiency of the company.This paper review and summarize the classification and characteristics of productionscheduling problems and the status of methods research. We set up a hybrid flow shopscheduling model base on real actual conditions, and build up the improved geneticalgorithms method to solve HFSP base on SGA method and FCFS rules after compare avariety of methods. Then we build a simulation model in Plant Simulation for HFSP toverify the performance of this improved genetic algorithms method.After that, using actual case of Schaffner company production line, this paper apply theimproved GA method on real scheduling to find the best sequence of the parts andverified by the simulation module which was set up in the Plant Simulation. Theimproved GA method has good convergence and stability which proved by comparingwith manual scheduling result and plant simulation result.