The Research On The Integrated Optimization Of Production Planning And Scheduling Of Multistage Manufacturing Workshop

The development of science and technology has brought about the growing productionscale of manufacturing industry and the more complex and changeable productionenvironment. Through the formulation of reasonable production plans and schedules,manufacturing enterprises can improve the utilization rate of machines, reduce the productioncost and minimize the completion time, thus boosting their production efficiency andeconomic benefits. At present, the hierarchical optimization algorithms are adopted to solvethe problems in production planning, but these algorithms have obvious shortcomings. Forexample, the generated production plan can not guarantee a feasible scheduling solution.Consequently, this thesis conducts research on the integrated optimization of productionplanning and scheduling in manufacturing workshops.Currently, the majority of manufacturing enterprises are using the multistagemanufacturing system whose subsystems can realize the processing, assembly and othermanufacturing processes, but the existing researches on the integrated optimization ofproduction planning and scheduling in manufacturing workshops are confined to thesingle-level workshops, the complete modeling research on some specific problems are notthorough enough. In order to solve this problem, this thesis studies the integrated optimizationproblem of production planning and scheduling for flexible job shop, analyzes the integrationmodel that production planning and scheduling is optimized at the same time. Further based onthe idea of integrated optimization of production plan and scheduling, the integratedoptimization model of production planning and scheduling of a multistage manufacturingworkshop production is established, which overcome the shortcoming of traditionalhierarchical decomposition method to make the production plan.Firstly, the integrated optimization model of production planning and scheduling for theflexible job shop with masses production and the preparation time in a kind of parts processingis established, providing the conditions that can ensure the continuous batch processing.Besides, a hybrid genetic algorithm (HGA) is proposed based on the improvement of codingstrategy, crossover operation and mutation operation of genetic algorithm, and an adaptiveparameters updating strategy is adopted in order to improve the efficiency of algorithms.Then, the integrated optimization problem of a kind of multistage manufacturing system with the serial connection of first-level job shop and first-level assembly workshop is furtherstudied. This model takes the constraint relationship between all levels of products and thetransportation time of products into account. Due to the complex solution of productionplanning and scheduling in multistage workshops, a inspiring genetic algorithm (IGA) basedon genetic evolution is thus put forward whose searching efficiency is improved through theheuristic rules. The experimental results of simulation and algorithm comparison prove theeffectiveness of the algorithm.