Cultural algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multi-objective optimization environments. On the other hand, portfolio selection problem (PSP) is a well-know 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.
Key words: Constraint programming, autonomous search, heuristic search.
CAs, Cultural algorithms; PSP, portfolio selection problem; EMO,evolutionary multi-objective; BOCA, bi-objective cultural algorithm; EVL, extended virtual loser; PF, Pareto frontier; MOEA, multi-objective evolutionary algorithms.
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