A Conservation Genetic Algorithm for Optimization of the E-commerce Logistics Distribution Path

Abstract

E-commerce is a business activity that uses modern information technology to process cash flow and logistics to achieve transactions. Under the e-commerce environment, an item can reach to the customer accurately is a key factor to enhance the company's image. Therefore, how to efficiently select the algorithm to solve the vehicle routing problem is an urgent problem to be solved. Aiming at the problems existing in the logistics distribution of e-commerce, this paper combines the genetic algorithm with the conservation algorithm based on the maximum travelable distance of the vehicle, and uses the conservation algorithm to generate the initial solution of the genetic algorithm, and constructs the conservation genetic algorithm to solve the e-commerce environment logistics distribution path optimization problem. The simulation results show that the conservation genetic algorithm is more globally optimal than the genetic algorithm.