Research On The Production Scheduling Optimization Methods For Tobacco Enterprises

With the continuous development of China's market economy, the production planning of tobacco enterprises which used to be controlled by government, is now transforming to market-oriented mode gradually, which means, the enterprise must schedule production plan according to contract needs. Moreover, enterprises should analyze the capabilities of production line and inventory, in order to arrange and adjust production plan properly. So it is meaningful to design an automatic system of Production Scheduling to help enterprises to improve productivity and strengthen their core competitiveness.Production planning problems are often complex nonlinear multi-objective programming problems with constraints. In consideration of the natural characteristic of practical production planning problems, we use hierarchical approach to analyze the process of production planning. We divide the model into two levels. The objective of the higher level is to distribute the aggregate demand among each factory properly, while The task of the lower level is to arrange the production schedules of every factory accurately and efficiently. The detail of each level is enriched, and an appropriate algorithm is developed and applied.To solve the NP-hard problem, we use the genetic algorithm to search optimized results. In the first level, considering the relatively large size of this problem, we adopt the spanning tree-based genetic algorithm to solve it. In the second level, we use the adaptive weight approach to optimize a multi-objective programming problem based on genetic algorithm.In this study, we take a practical case for example, and realize it by using Matlab 7.0. The results turn out to be feasible and satisfactory. Finally, we draw a conclusion that, our method would be helpful to decrease the production costs.