Study On The Dynamic Location Of City Distribution Center In Uncertain Environment

The amounts of logistics rapid increases with the speedy development of economy, but the costs grow with a disproportionate speed because of the behindhand conception and technology of distribution. As the closest part to the customer in logistics system, distribution center have to improve customer satisfaction with a the possible lowest cost, especially to city distribution center. Because of this, meticulous research and planning are necessary. As the key of strategic planning, it is deserved to put in more energy on the research of location, because logistics system will be seriously and chronically affected by a determined location decision. Vintage location decision will lead a smooth process from the collection of products to deliver them to customers, followed a ideal economy benefits.Based on this background, this thesis research around the location of the city distribution center in the uncertain environment, which can be divided into three parts.Firstly, theoretical section, including chapter one, chapter two. Summarizing the development and problems of city distribution center create the macro environment of this thesis; generalizing other reach on city distribution center lay the foundation and direction of this thesis.Secondly, model section, including chapter three and chapter four. Modeling dynamic location of city distribution center in uncertain environment. A mixed-integer nonlinear constrained planning model is established with the consideration of uncertain supply, uncertain demand and time requirement. Based on this model, a dynamic location decisions for a long planning period is design by dynamic programming.Thirdly, practice section, including chapter five. Combined with the actual situation of company D, location decision from2013to2020is researched. Both decisions of static state and dynamic state are calculate, and the comparing result express the significance of this thesis. During this paper, these facts are highlighted. First, the uncertainty of supply, demand and time requirement are included, which is more comprehensive and realistic. Second, the introduction of dynamic programming, which abstract decisions into points, and solve it with Floyd. Third, the aid of matlab and lingo, which expand the practicality and applicability.