.png){kind=icon}
返回
A GRASP based solution approach to solve cardinality constrained portfolio optimization problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cie.2015.10.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In the current work, a solution methodology which combines a meta-heuristic algorithm with an exact solution approach is presented to solve cardinality constrained portfolio optimization (CCPO) problem. The proposed method is comprised of two levels, namely, stock selection and proportion determination. In stock selection level, a greedy randomized adaptive search procedure (GRASP) is developed. Once the stocks are selected the problem reduces to a quadratic programming problem. As GRASP ensures cardinality constraints by selecting predetermined number of stocks and quadratic programming model ensures the remaining problem constraints, no further constraint handling procedures are required. On the other hand, as the problem is decomposed into two sub-problems, total computational burden on the algorithm is considerably reduced. Furthermore, the performance of the proposed algorithm is evaluated by using benchmark data sets available in the OR Library. Computational results reveal that the proposed algorithm is competitive with the state of the art algorithms in the related literature. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Portfolio optimization
Meta-heuristics
GRASP
Quadratic programming
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
引用论文
Reduced white matter microstructural integrity correlates with cognitive deficits in minimal hepatic encephalopathy轻度肝性脑病中白质微结构完整性降低与认知缺陷相关.png)
Gut
GutIF0
PREAI
分享收藏
查看更多内容