Abstract
When facing the problem of modern logistics distribution under the large-scale network, the reasonable delivery task allocation has become an important part. For this problem, this paper uses the idea of decentralized control to establish a region division model in logistics distribution and transforms it into the multiple traveling salesmen problem with constraints of the road network and task allocation. The optimization goal of the model is to minimize the sum of the distances for logistics transport agents traveling all demand points in the system, with the constraints on the equilibrium of commodity requirements in each sub region. Then, a two-stage algorithm is proposed to solve the model. In the first stage, the $K$ -means clustering method is used to obtain a highly feasible initial solution; In the second stage, the initial solution is optimized by the algorithm which is combining swap algorithm and tabu search algorithm. In the two-stage solution evaluation, the TSP solution based on the Lin-Kernighan algorithm is applied to obtain the sets of demand points with ranking of the route and the corresponding shortest distances for each divided sub region. Finally, to verify the effectiveness of the proposed model and solving method, two cases are presented in this paper. The region division method in logistics distribution proposed in this paper not only helps to reduce the total distance, but also helps to balance the workload of the logistics transport agents, thereby making great potential to reduce logistics costs and improving the overall operational efficiency of logistics distribution.
Highlights
Logistics distribution planning is a vital part of the modern logistics system
This paper compares the objective function, equilibrium ratio of commodity requirements, and calculation time of the four solutions to test the scientificity of the proposed model and algorithm
Facing the problem of modern logistics distribution under the large-scale network, there are more and more demand points. This requires multiple logistics transport agents to be responsible for the delivery tasks at the same time
Summary
Logistics distribution planning is a vital part of the modern logistics system. With the continuous development of Chinese economy, the commodity requirements have increased greatly, and demand points for logistics distribution are more and more widely distributed. (4) In the two-stage solution evaluation, the TSP solution based on the Lin-Kernighan algorithm is applied to obtain the sets of demand points with the ranking of the route and the corresponding shortest distances for each divided sub region. (1) The section of model construction presents the building method of the region division problem in logistics distribution; (2) In the section of algorithm design, a two-stage algorithm integrating the K -means clustering method, swap algorithm, tabu search algorithm, and LKH solver is proposed to solve this model. The remainder of this study is organized as follows. (1) The section of model construction presents the building method of the region division problem in logistics distribution; (2) In the section of algorithm design, a two-stage algorithm integrating the K -means clustering method, swap algorithm, tabu search algorithm, and LKH solver is proposed to solve this model. (3) In the section of case studies, we test the performance of the proposed model and algorithm in solving cases. (4) The last section summarizes the whole study and concludes with a discussion of future work
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