Optimization Research For Integrated Vehicle Routing And Vehicle Filling Problem In Logistics Distribution

With the rapid development of logistics industry, the effect of distribution becomes more and more important in the whole logistics system. In order to increase distribution efficiency, reduce distribution cost and serve clients better, many domestic and abroad researchers have been carrying a lot of research on many problems in distribution through modern ideas and methods. As Vehicle Routing Problem (VRP for short) and Vehicle Filling Problem (VFP for short) are two key problems in logistics distribution, they have become research hotspots certainly. For the sake of simultaneous optimizing vehicle distribution routes and vehicle filling projects, this paper combines these two problems which are related and restrictive each other in distribution and carries through integratation problem research on the basis of summarizing domestic and abroad research of VRP and VFP. There are two research emphases in this paper: (1) Building the new-style optimization model of integrated VRP&VFP; (2) Design one kind of algorithm which fits the solving integrated VRP&VFP optimization model by the improved genetic algorithm and solve the corresponding problem through the designed integrated optimization.Firstly, this paper summarizes modern research status of VRP and VFP, basic theory of logistics distribution and presents two objects which will be integrated, one is problem and model of VRP, the other is problem and model of VFP. In them, VRP is underloaded VRP and VRP is two-dimension VFP. On these bases, paper analyses and solves the problems met in integration course, presents integrated optimization problem of VRP&VFP and builds integrated optimization model of VRP&VFP. After accounting for the whole solving thought, paper makes a series of amelioration on basic genetic algorithm and designs the algorithm which fits the solving the integrated model.Then, paper detailedly and concretely designs every step in the algorithm. The design mainly aims VRP improved genetic algorithm section and VFP improved genetic algorithm section. In order to make the algorithm compact, efficientive and fit solving the VRP&VFP integrated optimization model, we improve many genetic algorithm steps in design, for example: introducing operation of preserving excellent individual, adopting methods of simultaneous decoding according to quality restriction and validating volume restriction,in the course of VRP decoding, for crucial difficulty in solving VFP, simultaneitive maximizing rate of quality loading and rate of volume loading, designing quality fitness function and volume fitness function and combining operation of preserving excellent individual to solve it, etc. After accomplishing the design of the two algorithm sections, they are perfectly combined together and make up of the solving algorithm. In the course of solving the integrated problem, they are interrelated, interinhibitive and indiscerptible. At the same time, MATLAB software is adopted to compile the corresponding software programs. The designed algorithm is realized by these software programs.Finally, the MATLAB programs which are compiled according to the solving algorithm are applied to solve corresponding practical problem. The progames gained very good and satisfying results in very short time. It has been proved that integrated VRP&VFP optimization model and algorithm are feasible, effective and valuable in practice.