PARALLEL UNIVERSES ALGORITHM: A METAHEURISTIC APPROACH TO SOLVE VEHICLE ROUTING PROBLEM

Meta-heuristic algorithms such as genetic and particle swarm optimization (PSO) algorithms have become suitable methods for solving complex optimization problems. This paper presents a new meta-heuristic algorithm called parallel universes. This algorithm is based on an unproven theory in physics called parallel universes. In this article, we first explain the essential steps of the algorithm and how it works. To prove the efficiency of our algorithm, we compare the results of our algorithm with the improved ant colony optimization (IACO), ant-weight strategy (ACO-W), the ant-mutation Operation (ACO-M) and improved ant colony system (IACS). We also examine the speed of convergence to the final solution by the algorithm. Comparing the solution provided by our algorithm with four other algorithms clearly shows the superiority of our algorithm in the final solution.