Research On Truck Sequence In A Cross Docking System Based On Ant Colony Optimization

With the development of economic globalization and e-commerce,the competition among enterprises is becoming increasingly fierce,but in order to enhance the competitiveness and market share,reducing the logistics costs is an effective way for companies to increase profits,which is a kind of cross docking scheduling can reduce costs,accelerate the effective strategy of distribution.With the development of network information and improve the quality of life,consumer demand has also increased rapidly,the required type of cargoes increased and volume reduced,then delivery trucks procurement or delivery once cargoes will have to go more suppliers or consumers.In this distribution mode,trucks are generally in a fixed sequence of purchase or distribution,in the center of cross-docking,the inbound truck will have a fixed unloading sequence order after the purchase of goods,the outbound truck will have a fixed loading sequence order before delivery the cargoes,So,in this paper,we study the sequence of trucks and the assignment of doors with a fixed unloading and loading sequence on cargoes,and our object is to minimize the makespan of cross-docking center.In this paper,the vehicle scheduling model is the inbound and outbound trucks having arrived at the center,sorting of inbound and outbound trucks then the trucks will be parked at the gate to unload and load the cargoes,the unloading or loading process of each truck cannot be interrupted,it is necessary to unload all of their cargoes or to load all the required cargoes before leaving the warehouse door,at this time,the idle warehouse door arranged for a car to stop loading and unloading operations.According to this problem,a mathematical model is established,and according to the number of doors,the number of trucks and the number of cargoes,the problem is divided into small,medium and large scale,and the ant colony algorithm and the improved ant colony algorithm are designed to solve the problem.First of all,the ant colony algorithm is used to design the problem,according to the characteristics of the algorithm and the actual situation of the problem,setting the key variables in the algorithm,the ant colony search method,update rules and calculation formula to solve the problem of three kinds of size,and analyze the influence of the parameters in the algorithm on solving practical problems.The results are compared with the results of genetic algorithm,ant colony algorithm is better than genetic algorithm insolving quality,compared with the genetic algorithm,the solution time is reduced by 54%.In order to improve the performance of ant colony algorithm,an improved ant colony algorithm is proposed,by improving the algorithm to search the rules of the truck,the initial solution of the heuristic,pheromone update mode and the value of pheromone control,the use of dynamic parameters to enhance the search space and convergence rate.Finally,the three scale problems are solved,and the experimental results are shown the improved ant colony algorithm is almost the same as the basic ant colony algorithm on the solution time,and superior to genetic algorithms.In solving the quality,the improved ant colony algorithm performs better than the basic ant colony algorithm,the highest increase of 7%.In this paper,we studied the problem of cross-docking based on ant colony optimization and provided theoretical support for the actual scheduling.