Szczegóły publikacji
Opis bibliograficzny
Agent-based co-operative co-evolutionary algorithms for multi-objective portfolio optimization / Rafał DREŻEWSKI, Krystian Obrocki, Leszek SIWIK // W: Natural computing in computational finance , Vol. 3 / eds. Anthony Brabazon, Michael O'Neill, Dietmar G. Maringer. — Berlin ; Heidelberg : Springer-Verlag, cop. 2010. — ( Studies in Computational Intelligence ; ISSN 1860-949X ; vol. 293 ). — ISBN: 978-3-642-13949-9. — S. 63–84. — Bibliogr. s. 83–84, Summ.
Autorzy (3)
- AGHDreżewski Rafał
- Obrocki Krystian
- AGHSiwik Leszek
Dane bibliometryczne
| ID BaDAP | 55311 |
|---|---|
| Data dodania do BaDAP | 2010-12-13 |
| DOI | 10.1007/978-3-642-13950-5_5 |
| Rok publikacji | 2010 |
| Typ publikacji | fragment książki |
| Otwarty dostęp |  |
| Czasopismo/seria | Studies in Computational Intelligence |
Abstract
Co-evolutionary techniques makes it possible to apply evolutionary algorithms in the cases when it is not possible to formulate explicit fitness function. In the case of social and economic simulations such techniques provide us tools for modeling interactions between social and economic agents-especially when agent-based models of co-evolution are used. In this chapter agent-based versions of multi-objective co-operative co-evolutionary algorithms are presented and applied to portfolio optimization problem. The agent-based algorithms are compared with classical versions of SPEA2 and NSGA2 multi-objective evolutionary algorithms with the use of multi-objective test problems and multi-objective portfolio optimization problem. Presented results show that agent-based algorithms obtain better results in the case of multi-objective test problems, while in the case of portfolio optimization problem results are mixed. © 2010 Springer-Verlag Berlin Heidelberg.
