Hybrid metaheuristic for Portfolio Selection: Comparison with an exact solver and search space analysis

In this paper we use a metaheuristic approach to solve the Portfolio Selection problem, in a constrained formulation which is NP-hard and difficult to be solved by standard optimization methods. We are comparing the algorithm´s performances with an exact solver and we are showing that different mathematical formulations lead to different algorithm´s behaviour. Results show that our approach can be efficiently used to solve the problem at hand, and that a sound basin of attraction analysis may help developers and practitioners to design the experimental analysis.