Abstract
This paper proposes a combination genetic algorithm (GA) for solving the combination optimization problems which can not be naturally solved by standard GAs. A combination encoding scheme and genetic operators are designed for solving combination optimization problems. We apply this combination GA to the portfolio optimization problem which can be reformulated approximately as a combination optimization problem. Experimental results show that the proposed combination GA is effective in solving the portfolio optimization problem. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Chen, J. S., & Hou, J. L. (2006). A combination genetic algorithm with applications on portfolio optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4031 LNAI, pp. 197–206). Springer Verlag. https://doi.org/10.1007/11779568_23
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