Integrated Modeling And Optimization Of Production Planning And Scheduling For Job Shop

Integrated optimization of production planning and scheduling is the core technology of enterprise production and management.It is also an important aspect of the enterprise competitiveness.The traditional production planning and scheduling method is "Top to down".At first,generate the production plan,and then,on the basis of the given production plan,produce the detailed scheduling.Main shortcomings of the traditional hierarchical method is due to ignore the detailed scheduling constraints on plan layer,makes a given production plan may not be able to obtain the feasible scheduling.Therefore,the ideal way is to integrate the production planning and scheduling optimization.Consider scheduling constraints to guarantee the plans feasibility,and optimize the planning and scheduling at the same time.Both address the imbalance of task demand in the whole plan and overcome the production of varieties changes too frequently in one cycle at the same time.Avoid the processing to prepare(or adjust)takes up too much time and reduce the utilization rate of equipments,production capacity and production efficiency.So in the background of JIT,this thesis researches Job Shop production planning and scheduling integrated optimization problem in small and medium-sized enterprise manufacture environment.Combined with a large number of domestic and foreign literature,this thesis studies and analyzes integrated optimization of job shop production planning and scheduling.In order to satisfy the multiple demands of integrated optimization goal in actual production planning and scheduling,this thesis sets up an integration model based on the decomposition method and suitable for mass production.Determine the comprehensive evaluation objective function based on production batch planning and processing time jointly.Minimize the sum of the whole project adjustment cost,inventory cost and production cost in the total planing,and ensure to minimize the makes pan at the same time.The constraint conditions including inventory balance and capacity constraints,the scheduling constraints,the operation sequence and work piece on a single machine processing capacity constraints must be considered to ensure the feasibility of the plan.In order to speed up the iterative,avoid precocious and ensure the operation stability at the same time,this thesis puts forward the integrated use of ant colony algorithm and the heuristic rules.This algorithm reduces the complexity in analyzing ant transition probability,and compares with the performance of the simulated annealing algorithm and genetic algorithm.The algorithm is used to simulate an example in integrated optimization problem of planning and scheduling.The results show that the algorithm is fast,strong convergence and good global convergence.Based on the above theory,applicate the proposed integration model and ant colony algorithm to an example,in JIT environment and the background of many varieties,small batch production workshop,the results of analysis shows that the given model and its solving method is feasible and the optimization result is far better than genetic algorithm wroted by NEH sort rules.