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Papers for this issue of China 's modern logistics vehicle scheduling efficiency is low , the cost is too high and can not adapt to the modern logistics more variety, small batch , multi- frequency , real-time visualization logistics trends , logistics vehicles as the main distribution tool enterprises to design a set of intelligent logistics vehicle scheduling system . The system mainly consists of two core parts: First , the vehicle routing to optimize layer , the layer application of ant colony algorithm to calculate every distribution vehicle , get the car to reach the optimal path of the delivery destination and its time ; fuzzy neural decision layer , the optimal path according to the specific situation of each vehicle (including the car to the distribution destination , time of arrival , the day of the cumulative total mileage , etc. ), the calculation of the vehicle 's overall satisfaction function value . Comprehensive satisfaction functions including customer satisfaction function , satisfaction of employee satisfaction function and cost function of three sub-functions of the system as a each subfunction to construct a mathematical model , and then using the compound fuzzy neural network case-by-case basis , the last three sub- function value weighted and get the comprehensive satisfaction function value of the vehicle . By comparison , the vehicles for optimal vehicle selected function value of overall satisfaction , the optimal path and dispatch instructions sent to the vehicle , optimal scheduling tasks . The system to fully take into account the impact of the three factors of the customers, employees , business efficiency vehicle scheduling , at the same time ensuring cost-effective to do the humane management , vehicle intelligent scheduling .
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