Beetle swarm optimisation for solving investment portfolio problems

The Journal of Engineering

Tingting Chen¹  Jun Teng³  Yongjian Zhu⁴ 

[1] Faculty of Science , Jiangsu University , Zhenjiang, Jiangsu, 212013 , People'Institute for Advanced Study, Nanchang University , Nanchang, Jiangxi 330031 , People'School of Computer Science and Communication Engineering, Jiangsu University , Zhenjiang, Jiangsu, 212013 , People's Republic of China

关键词: beetle antennae search;    artificial intelligence concept stocks;    BAS;    portfolio model;    optimisation problems;    investment environment;    global searching;    st;    ard PSO;    BSO algorithm;    beetle swarm optimisation;    st;    ard particle swarm optimisation;    investment portfolio problems;   

DOI  :  10.1049/joe.2018.8287

学科分类：工程和技术（综合）

来源: IET

【 摘 要 】

A portfolio model is established after analysing the investment environment of the artificial intelligence concept stocks in China. To reduce the risk of investment, the beetle swarm optimisation (BSO) is proposed. BSO, based on the beetle antennae search (BAS) and the standard particle swarm optimisation (PSO), is derived from the standard PSO but the update rules of each particle originate from BAS. In global searching, BSO, making the model get a lower value at risk, is more capable than standard PSO, which is easily trapped in local optimal defects. This study tries to solve portfolio model by using BSO algorithm. The results prove that BSO can do better in dealing with optimisation problems of constrained multi-dimensional functions.

【 授权许可】

CC BY