Fuzzy bi-objective particle swarm optimization for next release poblem

Abstract

In search-based software engineering (SBSE), software engineers usually have to select one among many quasi-optimal solutions with different values for the objectives of interest for a particular problem domain. Because of this, a metaheuristic algorithm is needed to explore a larger extension of the Pareto optimal front to provide a bigger set of possible solutions. In this regard the Fuzzy Multi-Objective Particle Swarm Optimization (FMOPSO), a novel a posteriori algorithm, is proposed in this paper and compared with other state-of-the-art algorithms. The results show that FMOPSO is adequate for finding very detailed Pareto Fronts.