Distribution Network Based On The Theory Of Complex Systems Optimization Study

As the main source bringing temporal and spatial value, distribution network of logistics system has become the focus of market competition. It's the most important base for companies to achieve top place in buyer market. Due to the complexity of distribution network, many models and algorithms established to optimize problems are complex and have the nature of NP. It's hard to get satisfactory scheme with them. While the bottom-up methodology of complex theory has provided a better way to deal with complex problems like distribution network.Making the viewpoint of systems engineering as stand and with proper understanding of modern logistics development, this thesis gives comprehensive and layered explanations to importance and complexity of distribution network and to the influences among internal and external factors in it by combining theoretical and empirical research. After three key problems of distribution network optimization including road network, distribution center location choice and vehicle routing are generally discussed, an optimization model of logistic distribution network based on complex system theory is put forward. This model has three folds: first, by integrating CA and GIS, an extended CA sub-model to search the shortest path from one node to all other nodes is advanced;second, by considering its building cost, traffic condition and function, a distribution center allocation sub-model is proposed by adopting an improved genetic algorithm;third, a sub-model aiming to solve vehicle routing problem is established with improved genetic operators, which can calculate the fittest number of distribution vehicles in the while of optimizing the routing order with time constraints.The whole model is applied to Xi'an Post distribution network to prove its validity and simulating the reality. The results show the optimization model could fairly reflect the fact and be good for reducing the distribution cost, improving logistic effective and optimizing the distribution network.