Application Of Data Mining Technology In Logistics Management

In this paper,the optimized path selection strategy based on genetic algorithm is applied to the logistics distribution management system to study how to select the appropriate transportation route to speed up the response to customer demand,improve service quality and reduce operating costs.In this paper,the various optimization algorithms currently available for path optimization problems are compared,and the advantages and disadvantages of various algorithms in the routing problem of logistics distribution are analyzed.Finally,the genetic algorithm is determined as the application algorithm of this paper,and it is carried out.Detailed research.This paper expounds the design and implementation of an improved genetic algorithm for vehicle routing problem(VRP),and successfully applies the algorithm to the logistics distribution management system module to realize the automation of logistics distribution route selection.Through the in-depth analysis of the vehicle routing problem,the "selection operator" and "mutation operator" are improved for the two most important factors of "population diversity" and "selection pressure" in the genetic algorithm,and the general inheritance The algorithm is compared.The results show that the improved algorithm has a faster convergence speed,the obtained optimal solution quality is higher,and the calculation result is stable.The improved optimal distribution route of the algorithm does not cross,and completely forms a loop.The vehicle's full load rate is limited,so the improved genetic algorithm is significantly better than the traditional genetic algorithm.Finally,a distribution decision subsystem was developed.The system encapsulates the improved genetic algorithm.The same interface form provides a reasonable distribution path for decision makers.It is the automation of the current logistics distribution system.