Vehicle Routing Problem with Ant Colony Algorithm and VRP-2opt Optimization

This article explores the ant colony algorithm for the Vehicle Routing Problem (VRP) with VRP-2opt optimization. The Vehicle Routing Problem involves finding the shortest possible routes for vehicles within time constraints while satisfying various operational limitations. The ant colony algorithm is a heuristic approach inspired by the foraging behavior of ants, which has been widely applied to solve complex routing problems. VRP-2opt serves as a local search improvement technique that refines solutions by systematically swapping path segments to reduce total distance traveled. Through pseudocode implementations, we demonstrate how artificial ants deposit pheromones to favor shorter paths while the 2-opt algorithm iteratively removes route crossings by reversing path segments between two nodes. This research provides deeper insights into the principles and applications of both algorithms, highlighting their significance in developing efficient vehicle routing solutions through combined metaheuristic and local search strategies.