GA-based Solution To Vehicle Scheduling Problem

Vehicle optimized scheduling is the core link in logistic delivery. Systematic research on the theories of VSP is the base of developing intensive logistic, building modern scheduling system, developing intelligent transportation system and expanding electronic commerce. So, researching on VSP has great meaning both theoretically and practically.There are six chapters in my paper. The main content is as follows:1. Introduce the Vehicle Scheduling Problem in logistic delivery, including: the research situation at home and abroad, existing problem and classification. At last, I propose the problem we need to solve.2. Introduce the relevant theories and methods that use to solve Vehicle Scheduling Problem. This chapter introduces the principium of heuristic algorithm and genetic algorithm particularly, and explains the reason why I choose GA to solve the problem.3. Solution to the loading & unloading integration Vehicle Scheduling Problem with full load. There are two sections in this chapter. One solves the problem that the transportation task is confirmed; the other solves the unconfirmed task situation. In each section, I analyze the problem, build a mathematical model and design GA solution, including: designing the structure of chromosomes and the fitness evaluation function, selecting genetic algorithm operators, and designing the termination conditions. After that we analyze the reasonableness and the validity of the coding solution, and put forward the adjustment solution for the unreasonable situation. At last we develop a testing experiment platform with visual basic 6.0, and verify the validity of the algorithm through experiments.4. This chapter solves the non-full load problem. There are also two sections. One solves the problem that the transportation task is confirmed; the other solves the unconfirmed task situation. The steps of the solution are the same as the last chapter.5. Combining the solutions of the last two chapters, this chapter proposes the solution to the loading & unloading integration Vehicle Scheduling Problem with full load & non-full load integration.6. Summarize and evaluate the conclusions, and propose the prospect.