Tobacco Commercial Enterprise Logistics Network Optimization System Design And Implementation

In recent years, with increasingly market competition and expected shrink of profit margin in the future, Chinese Municipal Bureau of Tobacco Monopoly, which is a state monopoly industry for a long time, is taking the greater crisis feeling and mission sense of reform and innovation. Tobacco industry has inherent advantages and urgent requirements for logistics network optimization. In logistics operation, tobacco logistics has the property of huge transport volume and high value per unit. At the same time, measurement and cost-volume accounting has been unified and accurate due to tobacco standardization. Therefore, there is a great promoting space in tobacco logistics efficiency and cost control. In network layout, tobacco logistics network is typically characteristic of densely covered nodes all over the country and multi-hierarchy owning to ministrative division in planned economy period. For all domestic tobacco enterprises, they have been confronting a key technical problem of how to balance the contradiction of cost reduction and service improvement through logistics network optimization technology. Logistics network optimization, as a core link in tobacco logistics modernization, has been becoming an effective method to solve this problem in the case of ensuring consumers' interests and quality of service levels. Currently domestic research on network optimization of tobacco commercial enterprises logistics still stays in a primary stage relatively. Tobacco commercial enterprises have not formed an advanced, effective and stable method to achieve the logistics optimization, thus making problem urgent to be solved.In view of industry characteristics and practical operations, this paper proposed a solution for network optimization of tobacco commercial logistics combined with the problem of connection routing optimization and logistics network location optimization. The paper mainly studied on the issues of location selecting of RDCs, network hierarchical classification, connection routing optimization, inventory calculation and operational cost keeping in logistics network model. Meanwhile, it separated the complicated network model of multiple RDCs into single ones and united them together, and built up a network model of tobacco commercial enterprises logistics based on multiple factors of cost constraints. It put forward the genetic algorithm based on improved density-based clustering screening method to solve this model. In the calculating process, firstly the research made use of improved density-based clustering method to exclude those of low-density nodes out of the optional nodes, and divide optional nodes into optional RDCs and optional TCDs to reduce the complexity; secondly, in order to meet the needs of different populations, it adapted the principles of genetic population classification to adjust the crossover operator and mutation operator according to the their different adaptability; finally it managed the population update in use of simulated anneal method to accelerate the convergence of the algorithm, so an optimal solution out of the local minimal region can be got. This paper took the business data of a provincial level tobacco commercial enterprises logistics to practice and verified our optimized solution, being content with the achieved results and proved our method with effectiveness and scientific meaning.This paper focused on the specific domain of tobacco commercial enterprises logistics and started from the point of the necessity and reality in solving a practical problem. It elaborated the main purpose of the network optimization technology. Hereafter, we studied the current research work on logistics network and distribution routing optimization technology, and generalized those content that we can make use of. Then we proposed our logistics network model adapting to the real business needs in view of logistics network and distribution routing optimization, and designed a genetic algorithm based on improved density -based clustering method in the light of this model. In the meanwhile, we developed an optimized decision-making system of tobacco commercial enterprises logistics and got satisfied with practical results. Finally the paper reviewed and summarized the whole research process and achievements, then analyzed some points of weakness, putting forward some future research objective and directions.