Models And Algorithms Of Multi-mode Transportation Problem Under Uncertainty

As the strategy of "One Belt And One Road" is put forward, China’s freight industry will usher in a golden development period, at the same time, with the coming of "Internet+" era, the third party logistics enterprises will face unprecedented challenges, the traditional single mode of transport cannot satisfy the development demand of freight market. According to the actual transportation situation, multi-mode transport can make full use of existing network of infrastructure and the advantage of various modes of transport, integrating transport capacity resources, meeting the transport demand as well as achieve the minimum total cost of transportation, the shortest delivery time and the maximum profit of third party logistics enterprise.This paper applies the multi-mode transport method into the actual freight transportation environment, analyzes the uncertain factors which existed in the process of multi-mode transport comprehensively, and according to constraints and goals of the transportation to establish the corresponding uncertainty optimization model and designs the algorithm, finally uses an example to verify the validity of the model and algorithm.The main work of this paper is as follows:1. Based on certain cities’s freight demand in a certain period, the paper describes the multi-supply multi-demand multi-product multi-mode transportation problem under uncertainty, puts forward a method to deal with the multiple uncertainty variables, and discusses how to use the total capacity of various modes of transport reasonably to ship goods from the supply to demand side with the minimum cost of transportation from the perspective of third-party logistics enterprises, and further constructs an interval fuzzy mixed integer programming model of the corresponding transportation problem. In addition, according to some uncertainty theories such as interval ranking theory, the fuzzy linear programming theory, and the fuzzy expected value theory, the uncertainty model is converted into a deterministic optimization model, and two kinds of heuristic algorithm are designed to solve the model.2. On the basis of the present situation that the demand sides are more and more strict with goods arrival date and some supplies send the goods on fixed period of time, this paper takes multi-demand and one supplier as the research object, studies the multi-time multi-mode transport problem with time limit under uncertain rates and capacity; establishes an interval 0-1 integer programming model,and transforms the uncertain model into a deterministic model by using the conversion method based on interval ranking; finally, taking the goods transport between Wuhan, Beijing, Nanjing, Chongqing as example to carry on the instance analysis, and verify the validity of the model.3. The multi-mode transport problem with transit transport and direct transport under uncertain supply and demand is studied. An fuzzy integer programming model is established, and the theory of fuzzy chance constrained programming is applied to solve the problem. Experimental results show that total cost of the mixed transportation form (both contains transit transport and direct transport) is reduced by 3.33% than the direct transport. In long distance transportation, priority should be given to the mixed transport which contains transit transport.