Research on inventory path optimization of VMI large logistics enterprises based on ant colony algorithm

Abstract

Based on the idea of vendor management (VMI) inventory, this paper focuses on the integration and optimization of transportation and inventory control in large-scale logistics system, so as to minimize the total cost of the logistics system. Aiming at the inventory path optimization of VMI large logistics enterprises, based on ant colony algorithm, an improved ant colony algorithm, namely ant colony system algorithm, is designed to solve the model. The algorithm model combines deterministic selection and random selection to obtain a comprehensive probability, and combines local and global pheromone updating. In this paper, we study a two-level supply chain system with multiple customers from one supplier and inventory routing problem. According to the characteristics of inventory routing problem, a single cycle inventory path optimization model with time window constraint based on stochastic demand is established. The goal is to minimize the total system cost, including inventory cost of downstream customers, system transportation cost and penalty cost for not meeting the time window. According to the characteristics of the model, the ant colony algorithm is selected as the optimization method, and the improved ant colony algorithm is designed to solve the example, and the feasibility of the algorithm and model is verified.