A Multi-objective PSO algorithm with transposon and elitist seeding approaches

In this paper, we propose a new Particle Swarm Optimization (PSO) algorithm called Elitist Seeding Multi-Objective Particle Swarm Optimization with Transposon (ESMOPSO-T) to multi-objective optimization. ESMOPSO-T improves both the exploitation and exploration ability of MOPSO based on the combination of the transposon and elitist seeding approaches. ESMOPSO-T is compared against three state-of-the-art Metaheuristic algorithms, including a PSO-based approach and two evolutionary algorithms. Results indicate that the ESMOPSO-T is highly competitive in both approximating the Pareto-optimal front and maintaining the diversity of the solutions on the front.