The Research Of Lot Sizing Production Planning Problem In Supply Chain

The lot sizing production planning in Supply Chain Management is a hard but to cracked that can not be obviated for batch production enterprises. Success or not is dependent on the knowledge of the lot sizing for a certain extent. Research on Supply Chain Management is carried with the market's demand as clue. Technologies as operational research, probability statistics, fuzzy programming and intellect algorithm are applied in this dissertation.The main contributions of this dissertation are shown as follows:1. By reading and collecting a lot of materials and literatures, the author finds out and concludes the existing research condition, problems of the lot sizing production planning in supply chain.2. Devise a genetic algorithm to solve the Economic Lot and Delivery Scheduling Problem-ELDSP, and compared with heuristic algorithm and polynomial time algorithm. Numerical examples are given to illustrate the genetic algorithm efficient.3. The lot sizing production planning in supply chain problem with fuzzy demand is studied in the paper. The influence of bullwhip effect and the average cost per time unit is minimized are considered in the model and translate into fuzzy chance constrains programming model. At last, an optimal algorithm and genetic algorithm based in the fuzzy simulation. The simulation examples indicate FS-GA's validity.4. Models with the optimal policy for the system as a whole under central control and decentralized control are proposed. Furthermore, devise a genetic algorithm and a branch-and-bound algorithm to solve the model under decentralized control. Numerical examples are given to illustrate the two algorithms efficient.