Research On Integrated Optimization Of Production Planning And Scheduling In A Flexible Job-shop

With the increase of production workshop complexity and the diversified demands of customers,production planning and scheduling have become two decisive challenges in the operation management of current manufacturing enterprises.At present,the conventional way utilized to solve the problem is to handle production planning and scheduling respectively.It has a distinct defect that project planning and scheduling decision can not match and coordinate.In order to avoid this drawback,the integrated optimization of production planning and scheduling with multi-variety and small batch in a flexible job shop(FJS)production environment is researched.In this thesis,taking batch planning,scheduling schemes,reasonable use and machine production capacity constraints of machines and other practical factors into further consideration,a more accurate and reasonable optimization scheme of production planning and scheduling is developed to realize the minimization of the total production cost and improve the utilization rate of production resources by adopting the lean production mode.Through the analysis of research results at home and abroad,the integrated thought of production planning and scheduling are studied considering current research status of existing problems.Furthermore,the overall coordination integrated modeling method is used as the integrated solution method,and the concept of micro plan is presented.A new integrated strategy which uses micro plan to realize the overall coordination of production planning problem and the scheduling problem is proposed.In this thesis,based on micro plan,an integrated coordination model of production planning and scheduling is established on basis of meeting the requirement including appropriate lot-sizing plan,reasonable procedure management,flexible machine dispatch and other constraints.Aiming at the constraints of planning layer,scheduling layer and integrated optimization performance indicators,the coordination structure of macro planning and scheduling decision is realized by micro plan.Moreover,the micro planning decision variables are introduced to solve the problem that the planning layer and the scheduling layer are difficult to coordinate with each other.Finally,while ensuring that the production tasks are completed on time,the resource utilization is improved and minimize total production cost is realized.In order to obtain the solution to the integrated coordination model established in this thesis,ahybrid genetic algorithm of embedded optimal particle swarm is put forward.The definite thought of the improved hybrid genetic algorithm is as follows.The first step is that the micro plan decision of coordination between macro plan decision and scheduling decision by utilizing hybrid genetic algorithm which is the core of the whole algorithm.The second step is that the optimization particle swarm is used to realize the process from scheduling decision obtained to new the micro plan decision.On this basis,the forward and reverse adjustments of the planning layer and scheduling layer are accomplished realizing the collaborated optimization of project planning and scheduling decision.In order to verify the integrated optimization scheme above and the validity of improved hybrid genetic algorithm,the algorithm parameters were determined by a certain number of experiments and the practical production typical case was selected.The model and algorithm proposed in this thesis were applied to multi-variety and small batch processing tasks in a machine tool factory for verification.Through the analysis of the operation results,the feasibility and correctness of the model and algorithm are proved.Then the in-depth comparative experiment of the algorithm is carried out,and it can be shown it has better accuracy,rationality and optimization in handling practical problems.