Research On Courier Scheduling Problem Based On Ant System With Back-to-Depot And Path-reform Behavior

In recent years,with the rise of online shopping,e-commerce and express logistics industry have developed rapidly."First-last Mile" as the end of logistics distribution is a process in which the couriers deliver items from distribution station to the customers,and the key to its efficiency lies in the rationality of courier scheduling.In actual scenarios,the delivery of many items often requires the assistance of multiple couriers.Unreasonable scheduling of couriers will cause an imbalance in the delivery distance between couriers.This imbalance will lead to the great gap between the waiting time of customers and the work load of couriers,which not only affects the preference for the enterprise service of customers,but also makes rest use of human cost.According to the above analysis,this paper requires to consider the balance of delivery distance between couriers based on minimizing the total delivery distance of couriers on the practical engineering problem of how to reasonably manage couriers to improve logistics distribution efficiency.This paper abstracts the above courier scheduling problem into a multiple traveling salesman problem based on multiple objective optimization.The main difficulties are as follows: Firstly,the traveling salesman problem is a typical NP-hard problem.The multiple traveling salesman problem is its expansion problem,the research difficulty of which has increased.On this basis,the combination with the multiple objective optimization problem has raised the difficulty of the problem to a higher level.Secondly,there are very few related studies to solve the above problem model,and the common algorithms based on heuristic search perform not well,because its heuristic information does not include the balance of delivery distance between couriers.In this paper,through a large number of experiments using ant colony algorithm,the above difficulties are verified and analyzed,and the improvement direction is provided for the ant colony algorithm to better solve the problem model.This paper proposes a novel ant colony algorithm—ant system with back-to-depot and path-reform behavior to better solve the courier scheduling problem.The improvement points of this algorithm are as follows: Firstly,the back-to-depot constraint strategy is applied to ant search,which limits the sub-path length by constraining the direction of ant movement according to the hypothetical sub-path length.Secondly,the stacked path-reform strategy is used to ensure the balance of the delivery distance between the couriers by neutralizing the longest sub-path and the shortest sub-path.Thirdly,the staged pheromone-update strategy is used to improve the quality of ant search by using the targeted pheromone update rules at different stages of ant search.According to the experimental data,the three improvedstrategies have effectively improved the performance of the ant colony algorithm on the two optimization objectives.According to the distribution characteristics of the community,the distribution position of the "First-last Mile" of e-commerce logistics was simulated,and several test samples were generated.The ant system with back-to-depot and path-reform behavior proposed in this paper,genetic algorithm,differential evolution algorithm,local search algorithm and simulated annealing algorithm were used in comparative experiments and the results show that the ant system with back-to-depot and path-reform behavior can search for a better solution to meet the engineering needs of courier scheduling problems in the "First-last Mile" of e-commerce logistics.