Research on the Bias Sampling RRT Algorithm for Supermarket Chain Distribution Routes under the O2O Model

Abstract

The purpose of this article is to propose the Bias Sampling RRT algorithm and use it as an optimization algorithm for supermarket chain distribution routes under the O2O model. As a retail store in the transformation and upgrading of chain stores, the actual terrain factors in distribution directly affect the timely delivery of goods from online to offline. The Bias Sampling RRT algorithm, as a path search method for time window vehicle routing problems, can find the optimal path that meets time window constraints. The applicability and effectiveness of the Bias Sampling RRT algorithm have been demonstrated through map simulation calculations. The simulation results show that compared with the RRT method, the Bias Sampling RRT algorithm has a shorter distribution path and shorter distribution time. This method is very suitable for the distribution activities of chain supermarkets or single store retail enterprises in the complex transformation and upgrading of actual terrain.