A Multiagent Approach for Metaheuristics Hybridization Applied to the Traveling Salesman Problem

This paper proposes a multiagent approach for metaheuristics hybridization inspired on the popular technique called Particle Swarm Optimization (PSO). In the proposed approach, agents develop a society with collaboration to achieve their own individual as well as common goals and their decision-making process matches the basic nature of a particle in the PSO framework. Each particle is an autonomous agent with memory and methods for learning and making decisions. The proposed approach is applied to the Traveling Salesman Problem in order to test its effectiveness.