Multiparty Coordinated Logistics Distribution Route Optimization Based on Data Analysis and Intelligent Algorithm

Abstract

Aiming at the shortcomings of traditional genetic algorithms such as premature and insufficient local search ability, a hybrid genetic algorithm combining k -means algorithm and cluster analysis to improve genetic algorithm is proposed. Among them, the selection operation adopts the tournament selection strategy of the elite retention model, the crossover operation adopts the double cut-point crossover, and the variation operator introduces the k -exchange variation operation to ensure the evolution of individuals from generation to generation. Through the selection, crossover, and variation operations, the objective function is minimized, the vehicle travel distance is greatly reduced, and the distribution route is optimized.