Multi-objective portfolio selection model with fuzzy random returns and a compromise approach-based genetic algorithm

作     者：Li, Jun Xu, Jiuping 

作者机构：Univ Elect Sci & Technol China Sch Management & Econ Chengdu 610054 Peoples R China Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Peoples R China 

出 版 物：《INFORMATION SCIENCES》 (信息科学)

年 卷 期：2013年第220卷

页      面：507-521页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China Youth Science and Technology Fund of university of electronic and science and technology of China NSFC National Science Foundation for Distinguished Young Scholars, P.R. China 

主　　题：Portfolio selection Multi-objective programming Fuzzy random variable Compromise solution Genetic algorithms 

摘      要：This paper addresses the multi-objective portfolio selection model with fuzzy random returns for investors by studying three criteria: return, risk and liquidity. In addition, securities historical data, experts opinions and judgements and investors different attitudes are considered in the portfolio selection process, such that the investor s individual preference is reflected by an optimistic-pessimistic parameter lambda. To avoid the difficulty of evaluating a large set of efficient solutions and to ensure the selection of the best solution, a compromise approach-based genetic algorithm has been designed to solve the proposed model. In addition, a numerical example is presented to illustrate the proposed algorithm. (C) 2012 Elsevier Inc. All rights reserved.