Extracting from the relaxed for large-scale semi-continuous variable nondominated frontiers

作     者：Steuer, Ralph E. Hirschberger, Markus Deb, Kalyanmoy 

作者机构：Univ Georgia Dept Finance Athens GA 30602 USA Munich Re D-80802 Munich Germany Michigan State Univ Coll Engn E Lansing MI 48824 USA 

出 版 物：《JOURNAL OF GLOBAL OPTIMIZATION》 (全局最优化杂志)

年 卷 期：2016年第64卷第1期

页      面：33-48页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：Multiple criteria optimization Portfolio selection Buy-in thresholds Nondominated frontiers Semi-continuous variables Parametric quadratic programming 

摘      要：Because of size and covariance matrix problems, computing much of anything along the nondominated frontier of a large-scale (1000-3000 securities) portfolio selection problem with semi-continuous variables is a task that has not previously been achieved. But given (a) the speed at which the nondominated frontier of a classical portfolio problem can now be computed and (b) the possibility that there might be overlaps between the nondominated frontier of the classical problem and that of the same problem but with semi-continuous variables, the paper shows how considerable amounts of the nondominated frontier of a large-scale mean-variance portfolio selection problem with semi-continuous variables can be computed in very little time.