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Top1. Introduction
Location selection has always been an important link in the supply chain. The location of logistics center is not only related to the service level of customers, but also directly affects the cost of the whole logistics process, so it has been paid great attention by scholars. At present, the research on location model mainly focuses on MCLP and CCLP. The problem of overlay is a classic problem of traditional location model. It was first proposed by literature and widely used in various fields.
The location problem of large-scale dynamic coverage is solved in detail by simulated annealing algorithm in reference (Regaieg, R., M Koubàa, Ales, Z., & Aguili, T. 2021). The algorithm can meet the service needs of 2500 nodes and 200 logistics hubs, and also fill the problem that previous researches have not paid enough attention to large-scale dynamic coverage. The paper (Aab, A., Ek, A., & Sr, B. 2021) proposes the multi-objective maximum coverage location and multi-objective fuzzy target planning based on the emergency vehicle positioning model. The ultimate goal is to improve service coverage and service level with a short total transportation distance. The paper (Ma, X., Yang, J., Sun, H., Hu, Z., & Wei, L. 2021) proposes the maximum coverage problem when both nodes and paths generate requirements, and establishes two different models for both requirements. Greedy algorithm based on simulated annealing algorithm is used to calculate the secondary maximum coverage position of node requirements, and geometric mathematics is used to calculate path requirements. Finally, the location of mobile service station in Yili County, New York is determined by tracking data of mobile users and mobile users. The paper (Attia, A. M., Al Hanbali, A., Saleh, H. H., Alsawafy, O. G., Ghaithan, A. M., & Mohammed, A. 2021) discusses the maximum coverage problem in the case of negative weight in the network, and proposes an integer programming algorithm for this problem, and implements the algorithm based on ILOG CPLEX software. The data set with 40 maximum coverage problems is solved and tested by two heuristic algorithms, ascending algorithm and simulated annealing algorithm. Reference (Jagadeesh, S., & Mu thulakshmi I. 2021) through the use of GIS and the elaboration of partial coverage idea, the traditional coverage model is extended to some extent, and the conclusion is that compared with the traditional coverage model, the new model covers more demand nodes. The paper (Abdel-Basset, M., Mohamed, R., & Mirjalili, S. 2021) propose a method of generating and covering the columns to solve the problem of maximum probability coverage.
The research on the location of maximum coverage in China in the early stage mainly focuses on the classification of the methods used and the reference for foreign scholars. The paper (Zou, F., Yen, G. G., Tang, L., & Wang, C. 2021) divides the covering location into two types: deterministic location model and probability location model. Deterministic location includes set coverage and maximum coverage. Probability location includes probability set coverage model, maximum expected coverage model and maximum availability coverage model. A membrane calculation method based on the non-uniform radius covering location is proposed in the literature (Ursulak, J., & Coulibaly, P. 2021), which is used to locate the fresh agricultural products logistics center. Reference (Shi, C., Wang, M., Yang, J., Liu, W., & Liu, Z. 2021) considers the location of the maximum coverage problem based on time satisfaction. Reference (Hm, A., Hw, B., Ye, T. A., Ran, C. C., & Xz, B. 2021) considers the location efficiency of joint coverage location at the lowest service level. Reference (Tam, N. T., Hung, T. H., Binh, H., & Le, T. V. 2021) according to the disaster degree of the disaster affected area, considering the factors such as the budget cost of the project in the disaster stricken area, the location model covering the largest problem is established to meet the needs of disaster relief and relief materials. Finally, through the actual numerical experiments, the influence area and materials meet different budget cost standards are discussed, Different influences on the number and address of the goods distribution center.