Study Of Tobacoo Commercial Company Distribution Network Design Based On Inventory Control

The tobacco industry is an important part of economy. However, highprofit of tobacco conceals problems such as excessive circulation parties,small scale, and high logistics fee. Currently, distribution center of tobaccocommercial companies is in large number. Distribution network layout isnot reasonable and inefficient in resource allocation. Moreover, due todifferent demand, inventory management cost is high to maintain servicelevel. The effect of “cost trade off” exists in distribution network design.But recently research related to inventory and location joint optimization isless. Thus, how to scientifically locate distribution centers and optimizeinventory management using logistic network optimization technique is apressing problem for tobacco commercial companies.The thesis firstly states current logistics esp. distribution developmentsituation of tobacco industry. It raises research content and targets based onrelated research at home and abroad. Then, it presents three distributionnetwork design steps:(1) network structure: supplier to RDC to transferstations (city and country);(2) multi criteria inventory classification modeltargeting to minimize inventory cost and diversity degree;(3) distributioncenter location model targeting to minimize total cost including inventory,transportation and construction cost. Implementation steps of AdaptiveSimulated Annealing Genetic Algorithm are design to solve the model.After that, empirical analysis gives results: Pareto solution sets includinginventory classification and different order cycles (model1), distributioncenter number and location, connection of all network nodes, total cost and cost breakdown(model2). The optimum proposal is an integration ofinventory control and network design. The result is satisfactory, whichproves that tobacco distribution network design method in the thesis isscientific and efficient. Finally, it concludes the research process andresults, and gives future research direction.