Research On Vehicle Scheduling Problem Of Non-full Loads Based On Genetic Algorithm

Logistic distribution is an operation linking with consumer directly, and takes account for considerable proportion in variable costs in logistics. The planning of vehicle scheduling in distribution will be take great effect on the efficiency, cost , and benefit, especially in distributing for mufti consumers. A scientific and reasonable method to vehicle scheduling is an important operation in logistic distribution. So, vehicle routing and scheduling problem had become focus of many scholars to study. In the developed commercial society with popularization of Internet and development of electronic commerce, requirement of consumer for delivery time is higher and higher so that delivery day formerly had turn to delivery hour now.First, different vehicle routing problem of delivery are classified according to their complexity. Second, in terms of the restrains and objective, an optimal integer-scheduling model in typical VRP is introduced. VRP is a typical strong NP-hard problem, high effective exact algorithm is imposable to it. Heuristic Algorithm can resolve large-scale problem, but cannot ensure the quality of the resolution. Recently, genetic algorithm has been tried to resolve variable combinatorial optimization problems.This paper attempts to take VRP with time window as the tow core problems for further research. On the VRP with time window, while the restraints of capacity and time windows are changed into object restraints, a mathematic model is established We use technique such as maximum preserved crossover and self-adaptability change of probability of crossover and mutation, and design genetic algorithm on nature number, which can deal with soft and hard time windows. The excellent solutions are obtained in the application.