A Hybrid Non-dominated Sorting Genetic Algorithm with Local Search for Portfolio Selection Problem with Cardinality Constraints

Abstract

ARTIGO ACEITO The Cardinality-Constrained Portfolio Selection Problem (CCPSP) consists of allocating resources to a limited number of assets. In its classical form, it is represented as a multi-objective problem, which considers the expected return and the assumed risk in the portfolio. This problem is one of the most relevant subjects in finance and economics nowadays. In recent years, the consideration of cardinality constraints, which limit the number of assets in the portfolio, has received increased attention from researchers, mainly due to its importance in real-world decisions. In this context, this paper proposes a new hybrid heuristic approach, based on a Non-dominated Sorting Genetic Algorithm with Local Search structures, to solve PSP with cardinality constraints, aiming to overcome the challenge of achieving efficient solutions to the problem. The results demonstrated that the proposed algorithm achieved good quality results, outperforming other methods in the literature in several classic instances.