Supply Chain Distribution Network Optimization Technology Based On Data Mining

With intensifying global competition, progress on science and technology, and evolution of modern management ideology and means, for the purpose of improving customer satisfaction and enhancing their core competitiveness, more and more enterprises are starting to pay attentions on the optimization performance of the Supply Chain Distribution Network to guarantee the rapid response and change of the supply chain system, the support of improvement of overall performance and the capability of supply chain system and the win-win situation of the individual income.In respect of locating the Supply Chain Distribution Networks, optimal configuration of products, operation and further optimization of products, this paper will follow the outline of "research on locating the Supply Chain Distribution Networks, research on optimal configuration of products, research on optimization of selecting location for flow sections of Supply chain retailing network, and research on further optimization of Supply chain retailing network". Some models and algorithms are established to address the issues mentioned above. The main contribution of this thesis includes the following aspects.1) Aiming at locating the customer- group oriented facility of the Supply Chain Distribution Networks, the cluster analysis methods of data mining are adopted, including introduction of cluster validity function and division of fuzzy degree, combining the partition entropy and partition fuzzy degree, giving"sum"cluster validity function, giving modified partition fuzzy degree as cluster validity function. This paper introduces the weight parametersλfor the assification attributes to control the influence of process of clustering from numerical attribues and classification attributes of the classification. Because the effectiveness of the cluster can be transformed into the best category number k, parameter selection method based on modified Partition fuzzy degree is proposed to study the determination method for optimal site chosen number corresponding to the cluster of customer data sructure to deal with the problem from numerical data, attribute data and mixed data type in customer group.2) Aiming at the characteristics of supply-chain, considered the customer preferences sequence data, analysis is carried out to determine whether a cluster exists for customer's mind tendency for multiple evaluation objects. This paper creates association relation model relating customer preferences and customer characteristic attributes. Borrowed cluster method for the symbol sequence in data mining, corresponding properties of the data from type symbol sequence are studied. The reasearch follows two directions, formal and instantiation, to discuss similarity issues of symbol sequence in which essential problems in cluster from preference symbol sequence clustering are analized. In addition, this paper also studies on how to apply self-organizing feature map as a symbol of the sequence clustering algorithm, and compares clustering model.3) As for the service facility location problem for customers, location selection problem relating retail network flow supply chain with dual capacity constraints and time-price constraints and the heuristic algorithm is given, in which the problem is transformed into a traditional CFIFLP issue to deal with. In view of the market demand has been fine segmented and retail network location selection for the supply chain for the customer flow that accepts detour distance, retail network location selection for the supply chain with route requirement and service radius is atudied, in which a greedy algorithm to solve the problem, local search algorithm, as well as taboo algorithm are given and compared. Research on more uncertain circumstances demand Flow Interception Facility Location Problem, and established a model and MAXMIN-FIFLP model, and gives a heuristic algorithm.4) Aiming at the situation of competition in the market, this paper studies the optimal location selection problem when the consumption capacity of the on road customers expanded. Competitive Capability Line Expand CCLE-IFIFLP model and heuristic algorithm have been proposed. Futther, location selection problem that maximizes the market share under the competitive environment is studied by introducing incremental demand rate and distance discount caused by competitive facilities cluster to describe cluster effects. In this paper, the model has been created, and the branch and bound algorithm and the greedy algorithm are used to solve this problem. The growth rate of demand discount and distance discount rate have been analized to determine the effects to the loation selection decision. To solve the customer satisfaction problems in the supply chain, customers'time satisfaction rate is used as coverage radius to discuss the distribution optimization problem in the supply chain based on time satisfaction rate maximized coverage the model and the corresponding heuristic algorithm are given.To verify the theoretical research results, the models and algorithms presented in this paper are implemented in the Weihai-HAIDU food industry information project as a typical application use case, in which product analysis, channel analysis and market analysis for the distribution network of supply chain. Application and the testing results are given and the theory proposed in the paper is verified.