Decision support for vehicle dispatching using genetic programming

Vehicle dispatching consists of allocating real-time service requests to a fleet of moving vehicles. In this paper, each vehicle is associated with a vector of attribute values that describes its current situation with respect to new incoming service requests. Using this attribute description, a utility function aimed at approximating the decision process of a professional dispatcher is constructed through genetic programming. Computational results are reported on requests collected from a courier service company and a comparison is provided with a neural network model and a simple dispatching policy.