An evolutionary multi-objective optimization algorithm for portfolio selection problem

International Journal of Physical Sciences

Guillermo Cabrera G.¹ 

关键词: Constraint programming;    autonomous search;    heuristic search.;   

DOI  :  10.5897/IJPS11.813

学科分类：物理（综合）

来源: Academic Journals

【 摘 要 】

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.

【 授权许可】

CC BY