Research On Logistics Distribution Problem Based On STASA Algorithm

With the rise of the e-commerce industry,the express logistics industry has ushered in vigorous development.Nowadays,various express companies such as SF Express,JD Logistics,Cainiao Station,etc.are always transporting our express delivery,bringing a lot of convenience to our lives.However,we have also encountered many problems in express transportation such as loss or mis-delivery of express delivery,delays in delivery,and timeliness of logistics information.These problems not only seriously affect the customer experience,but also increase the cost of the logistics industry.In response to the above problems,this paper conducts an in-depth study on the basic discrete mathematical model of logistics distribution—Multiple Traveling Salesman Problem(MTSP),and redesigns the State Transition Simulated Annealing Algorithm(STASA)to solve the model.The specific research content is as follows:(1)In this paper,the STASA algorithm is used to solve and analyze the multiple traveling salesman problem(MTSP).According to the characteristics of the MTSP problem,on the basis of the STASA algorithm,a new STASA discrete transfer operator-Elementary Breakpoint Operator(EB)is proposed,which can quickly and accurately generate the candidate solutions of MTSP through a matrix operation and increase the diversity of solutions.(2)In order to reduce the phenomenon of route crossing and collision in the MTSP problem,the neighborhood search structure 2opt algorithm is introduced into the local search structure of STASA,and a new hybrid intelligent algorithm(STASA?2opt)is proposed.This algorithm improves the globality and optimality of the STASA algorithm.In order to verify the performance of the proposed algorithm,this paper tests the STASA?2opt algorithm on 12 large,medium and small-scale problems of MTSP.The experimental results show that the STASA?2opt algorithm has higher efficiency and better performance in solving MTSP problems.(3)On the basis of solving the MTSP problem,the MTSP problem is extended to a vehicle path planning problem with capacity constraints(CVRP)and a new solution scheme of STASA?2opt is designed.Firstly,the fusion design of the exchange,translation,symmetry,and elementary breakpoint transfer operators of the STASA?2opt algorithm is carried out,and a hybrid operator is proposed to expand the search space of the CVRP problem.Then,the dynamic adjustment strategy is adopted to select the operator.This strategy improves the search efficiency of the STASA?2opt algorithm and avoids blind search.Finally,according to the experimental results on 14 classic examples and 20 large-scale CVRP problems,the generalization ability of the proposed algorithm and the effectiveness and practicability of the STASA?2opt algorithm to solve the CVRP problem are proved.