Fourth Party Logistics Routing Problem With Fuzzy Duration Time

With the development of science and technology, many companies find it hard to get profit by improving their technology or optimizing industry process. As another way to get profit, logistics has been attracting more and more attention in many relative fields. As Fourth Party Logistics (4PL) plays an important role in modern logistics, many researches have been conducted on4PL ever since it was introduced, and many achievements have been done.Routing problem is one of the most important issues in4PL. There have been many valuable researches for Fourth Party Logistics Routing Problem (4PLRP), but few of them consider the uncertainty in the logistics process. In a real-world situation, driving conditions could be effect on many factors like weaher, human factors and so on. In the traditional way, researchers tend to use the stochastic optimal methods. But in some conditions, it is hard to describe the parameters of the problem as random variables because there are not enough data to analyze. In this situation, fuzzy variable is suitable to deal with these uncertainty parameters. On the other hand, the method for solving determinated4PLRP may be not very suitable for solving fuzzy4PLRP. It is necessary to do some researches on the characteristics of fuzzy4PLRP and to design effective models and algorithms for it. In this condition, a series of4PLRP with Fuzzy duration time (4PLRPF) are analyzed thoroughly. The main contents of the dissertation are as follows:(1) Research on single source to single destination single task4PLRP with fuzzy duration time.Based on the foundation of fuzzy theory, Single sourc to Single destination, Single task4PLRPF, called S-S-S4PLRPF, is presented, which is to find a route of the minimum due date with the cost, ability and reputation constraints under the uncertain environments. For solving the problem, firstly, we get rid of the node and edge that have not enough ability or reputation. Secondly, two kinds of fuzzy programming models are built under fuzzy theory, and fuzzy simulations are given for getting the crisp equivalent models. In order to solve the problem, K-shortest path algorithm embedded Genetic Algorithm (KGA), K-shortest path algorithm embedded Two step Genetic Algorithms (KTGA) with fuzzy simulation method and enumeration method are proposed. Numerical experiments are carried out to investigate the performance of the proposed algorithm on a set of S-S-S4PLRP instances. It can be seen that they are two effective algorithms for solving4PLRP.(2) Multi-source to Multi-destination, Multi-task4PLRPF is presented.The problem is to solve any number of source, destination and task4PLRPF, called4PLRPF for short. A4PLRPF credibility model is presented, which is to find a route of the minimum due date with constraints. In order to solve the modeled4PLRPF, K-shortest path algorithm, Self Organizing Migrating algorithm and Genetic Algorithm (KSOMGA) with fuzzy simulation method are integrated to find approximate optimal solutions. The experimental results show that the proposed method is effective.(3)4PLRPF with Cost discount (4PLRPFC) is studied.From the viewpoint of a4PL provider, by considering the comprehensive capacity of Third Party Logisitics (3PL) suppliers and transit nodes, the4PLRPFC is described and a credibility model is established. According to the characteristics of the model, K-shortest path algorithm embedded Memetic Algorithm (KMA) and enumeration method are designed. The numerical experiments show that the proposed algorithm has the advantages both on the quality of the results and the time of computation.(4)4PLRPF by considering the Travel schedule (4PLRPFT) is investigated.Based on the above investigation, for the transit which needs to wait for departure time in the transportation problem, from4PL provider’s point of view, by considering the comprehensive capacity of3PL suppliers and transit nodes, and the traveling schedules,4PLRPFT is built. After the conversion from the’time point’to the’time section’, ant colony optimization algorithm is designed. Numerical experiments show the effectiveness of the algorithm and it reflects the real situation of transit by considering travel schedule.(5) An experimental system for4PLRPF is designed.An interface of the4PLRPF experimental system is developed by Microsoft Corporation C#. With the help of mixed programming method, we realized the background program called the front-end interface. In the experimental system, the realization process of4PLRPF,4PLRPFC and4PLRPFT are demonstrated, which will do some contribution to the further application.