An intelligent strategy of vehicle scheduling based on fuzzy-neuron networks

Abstract

A brand new intelligent system of vehicle scheduling is proposed and applied to the logistics companies whose service is transportation with vehicle. The key technology of this system is a compound fuzzy-neuron networks. First, a synthetically satisfied function is conceived. Then it is divided into three sub-functions. Each sub-function is each based on its own fuzzy rules and realized by a compound fuzzy-neuron networks. The final value of each vehicle is the sum of each sub-function multiplying its own right. The selective car which has the highest value is the vehicle to receive the scheduling order.