An evolutionary multi-objective optimization algorithm for portfolio selection problem

GUILLERMO NICOLAS CABRERA GUERRERO, Claudia Vasconcellos, RICARDO JAVIER SOTO DE GIORGIS, Jose Miguel Rubio, Fernando Paredes, BRODERICK CRAWFORD LABRIN

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Cultural algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multiobjective optimization environments. On the other hand, portfolio selection problem (PSP) is a wellknow problem in literature. However, only a few articles have applied evolutionary multi-objective (EMO) algorithms to these problems and articles presenting CAs applied to the PSP have not been found. In this article, we present a bi-objective cultural algorithm (BOCA) which has been applied to the PSP, and obtaining acceptable results in comparison with other well-known EMO algorithms from the literature. The considered criteria of the problem are risk minimization and profit maximization. The different solutions obtained with the BOCA have been compared using max-delta-area metric.

Original languageEnglish
Pages (from-to)5317-5328
Number of pages12
JournalInternational Journal of Physical Sciences
Volume6
Issue number22
StatePublished - 1 Jan 2011

Keywords

  • Autonomous search
  • Constraint programming
  • Heuristic search

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