| As the logistics industry comes to the globalization,information and integration times,the distribution is becoming increasingly important role in the entire logistics system.Among them,whether the transport routes are reasonable directly affects the costs and benefits of the distribution.Selecting the appropriate vehicle routing program can improve the service quality,enhance the degree of the satisfaction of the customer.Therefor,the vehicle routing problem has got great attention of the logistcs scholars and enterprises.The traditional vehicle routing problem only considers the simple pick-up or delivery process during the operation.The vehicle routing problem with backhauls most requested that the delivery service node be served earlier than the pick-up service node, that is,the vehicle completes the delivery task only in the distribution process while completes the pick-up task during the backhauls.So,not considering the delivery and pick-up as a whole caused the circuitions route and increased the transportation costs. The VRPSDP this paper studied didn't have the service order requirement,can reduce the transport vehicle distance and improve the effectiveness of the enterprise operation.This paper first discussed the basic theory of the vehicle routing problem and its common algorithm,on this basis,established the multi-objective VRPSDP mathematical model under the consideration of the minimum of the number of the vehicle and the transportation costs,identified the Genetic Algorithm as the solving algorithm of the model in this paper,designed the chromsome encoding and genetic operators that were more suitable for the VRPSDP.Finally,abtained the optimal objective function value and the arrangement respectively by the basic GA and the improved GA for the vehicle routing program with the simulation of the amended Solomon R101 instance,and validated the effective and rationality of the model and its solving algorithm by comparative analysis. |
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