DESIGN OF A ROUTING SIMULATION MODEL USING ANT OPTIMIZATION

Abstract

The rapid growth of freight transportation and courier services driven by e-commerce development has made route optimization particularly crucial for reducing logistics costs. This issue is especially relevant for Russia with its vast territories and complex transport infrastructure. The study addresses the routing problem, which belongs to the class of NP-hard problems, where traditional methods (e.g., branch and bound) prove inefficient for large-scale delivery networks. We propose a simulation model based on the ant optimization algorithm, implemented in the AnyLogic environment. The model utilizes pheromone trail mechanisms and heuristic data for adaptive route optimization, accounting for dynamic changes in transport networks. Experimental studies conducted on a GIS map of Eastern Siberia (15 cities) demonstrated about 30% reduction in route length compared to existing solutions. The results confirm the effectiveness of the proposed approach for optimizing logistics processes in large-scale regional contexts.