Large-scale Logistics Distribution Path Planning For Community Group Buying Based On An Improved ALNS Algorithm

In recent years,community group buying,as a new online group buying mode,has come into people’s sight.In the community group buying mode,with the increasing number of leader points,daily ordering customers and orders,it will cost a lot of time and energy to manually arrange vehicle routes.It is urgent to develop an efficient and reasonable vehicle route planning algorithm to replace manual routing.From the perspective of community group buying,a new e-commerce enterprise in China,this paper takes the terminal logistics and distribution link as the research object and studies the new vehicle routing problem of community group buying logistics and distribution route planning.The research content mainly includes the following aspects.To facilitate the community group buying logistics distribution path planning problem to solve,this paper combined with the actual scene to analyze the problem and build a model.Taking a community group buying electricity company smart wiring project as the background,analyzes the actual scenario community group buying the characteristics of logistics distribution path planning,combining history rows of results data,examines the vehicle fixed cost and total distribution cost from these two goals,and from the perspective of delegation and examines the colonel satisfaction of delivery time and group matching rate of the two evaluation index,establish the corresponding mathematical model.Through analyzing the mathematical model of community group buying logistics distribution path planning,IALNS algorithm(Improved Adaptive Large Neighborhood Search,IALNS)is proposed to solve the problem based on the actual problem.Specific improvements of IALNS algorithm include: Based on the characteristics of community group buying,the initial solution is pretreated and constructed,randomness is introduced to destroy strategy and repair strategy to increase the diversity of neighborhood search space,and relevant removal operators and repair operators are designed.Improve strategy is added on the basis of ALNS algorithm and corresponding adjustment operators are designed.In order to test the performance of the proposed IALNS algorithm,the validity analysis and performance test of the proposed IALNS algorithm are carried out using the Solomon common VRPTW example set.For R class examples with random distribution,the GAP value is within 2.9%with the known optimal solution and is consistent with the known optimal solution in examples R203 and R205.The class C examples of cluster distribution are consistent with the known optimal solution.For the RC example with mixed distribution,the GAP value is kept within 1.9% with the known optimal solution and is consistent with the known optimal solution in RC106,201,204,207.Then,the effectiveness of IALNS algorithm in improvement is analyzed by comparing with the results of classical ALNS algorithm.In addition to examples R201 and RC205,the solutions of IALNS algorithm were superior to those of classical ALNS algorithm or the results were the same.In this paper,the intelligent line arrangement project of a community group buying e-commerce company is taken as the background,and the business scene is simply described.Desensitization examples are extracted in line with the actual situation,and the corresponding experimental analysis is carried out with different algorithms to solve the actual calculation examples.The IALNS algorithm is compared with the classical ALNS algorithm,the improved Firefly algorithm(IFA),the hybrid genetic variation neighborhood search algorithm(HGA-VNS)and the artificial routing path planning results.IALNS algorithm has more advantages both in terms of solution quality and algorithm optimization time.It shows that IALNS algorithm is feasible to solve the problem of route planning of large-scale logistics in actual community group buying.