A Hybrid Intelligent Algorithm for Optimal Birandom Portfolio Selection Problems | Zendy

Qi Li | Zendy; Guohua Cao | Zendy; Dan Shan | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Hybrid Intelligent Algorithm for Optimal Birandom Portfolio Selection Problems

Author(s) -

Qi Li,

Guohua Cao,

Dan Shan

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/213518

Subject(s) - selection (genetic algorithm) , computer science , genetic algorithm , portfolio , hybrid algorithm (constraint satisfaction) , algorithm , computation , mathematical optimization , function (biology) , artificial intelligence , machine learning , mathematics , finance , constraint satisfaction , probabilistic logic , economics , constraint logic programming , evolutionary biology , biology

Birandom portfolio selection problems have been well developed and widely applied in recent years. To solve these problems better, this paper designs a new hybrid intelligent algorithm which combines the improved LGMS-FOA algorithm with birandom simulation. Since all the existing algorithms solving these problems are based on genetic algorithm and birandom simulation, some comparisons between the new hybrid intelligent algorithm and the existing algorithms are given in terms of numerical experiments, which demonstrate that the new hybrid intelligent algorithm is more effective and precise when the numbers of the objective function computations are the same.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research