A Hybrid Multiobjective Bat Algorithm for Fuzzy Portfolio Optimization with Real-World Constraints

被引:38
作者
Chen, Wei [1 ]
Xu, Wen [1 ]
机构
[1] Capital Univ Econ & Business, Sch Informat, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Portfolio selection; Fuzzy variables; Multiobjective optimization; Bat algorithm; Differential evolution; SELECTION; MODEL;
D O I
10.1007/s40815-018-0533-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates a fuzzy portfolio selection problem in the framework of multiobjective optimization. A multiobjective mean-semivariance-entropy model with fuzzy returns is proposed for portfolio selection. Specifically, it simultaneously optimizes the return, risk and portfolio diversification, taking into account transaction costs, liquidity, buy-in thresholds, and cardinality constraints. Since this kind of mixed-integer nonlinear programming problems cannot be efficiently solved by the conventional optimization approaches, a new metaheuristic method termed as the hybrid BA-DE is developed by combining features of the bat algorithm (BA) and differential evolution (DE). In order to demonstrate the effectiveness of the proposed approaches, we also provide a numerical example.
引用
收藏
页码:291 / 307
页数:17
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