An Improved Genetic Algorithm for Routing of Logistics Vehicles

Abstract

As the logistical industry is increasingly global and integrated with information technologies, distribution of goods plays a bigger role in the logistics system overall. In this context, choosing an appropriate route for delivery of goods is considerably helpful in shortening the response time to customer needs, improving service quality, increasing customers’ satisfaction and reducing operation cost. In-depth studies are conducted on the vehicle routing problem (VPR), which is critical to efficient delivery of goods. A multi-constrained mathematical model is established. Meanwhile, the traditional genetic algorithm is improved by constructing chromosome for feasible path through integer coding, introducing penalty term to fitness function. The proposed algorithm is implemented on Visual Studio 2010. The results demonstrate the effectiveness and feasibility of the proposed algorithm.