Randomized time-varying knapsack problems via binary beetle antennae search algorithm: Emphasis on applications in portfolio insurance

被引：31
|
作者：
Medvedeva, Marina A. [1 ]
Katsikis, Vasilios N. [2 ]
Mourtas, Spyridon D. [2 ]
Simos, Theodore E. [3 ,4 ,5 ]
机构：
[1] Ural Fed Univ, Grp Modern Computat Methods, Ekaterinburg, Russia
[2] Natl & Kapodistrian Univ Athens, Div Math & Informat, Dept Econ, Athens, Greece
[3] South Ural State Univ, Digital Ind REC, Chelyabinsk, Russia
[4] Neijing Normal Univ, Data Recovery Key Lab Sichun Prov, Neijiang, Peoples R China
[5] Democritus Univ Thrace, Dept Civil Engn, Sect Math, Xanthi, Greece
来源：
MATHEMATICAL METHODS IN THE APPLIED SCIENCES | 2021年 / 44卷 / 02期
关键词：
Knapsack problem; meta-heuristic optimization; portfolio optimization; time-varying integer linear programming; MONARCH BUTTERFLY OPTIMIZATION; COMPUTATIONAL METHODS; MODEL;
D O I：
10.1002/mma.6904
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The knapsack problem is a problem in combinatorial optimization, and in many such problems, exhaustive search is not tractable. In this paper, we describe and analyze the randomized time-varying knapsack problem (RTVKP) as a time-varying integer linear programming (TV-ILP) problem. In this way, we present the on-line solution to the RTVKP combinatorial optimization problem and highlight the restrictions of static methods. In addition, the RTVKP is applied in the field of finance and converted into a portfolio insurance problem. Our methodology is confirmed by simulation tests in real-world data sets, in order to explain being an excellent alternative to traditional approaches.
引用
收藏
页码：2002 / 2012
页数：11
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