A new evolutionary algorithm based on MOEA/D for portfolio optimization

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

7 Scopus Citations
View graph of relations

Author(s)

  • Heng Zhang
  • Yaoyu Zhao
  • Feng Wang
  • Anran Zhang
  • Pengwei Yang

Detail(s)

Original languageEnglish
Title of host publicationProceedings of 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)
PublisherIEEE
Pages831-836
ISBN (Electronic)978-1-5386-4362-4
Publication statusPublished - Mar 2018
Externally publishedYes

Publication series

NameProceedings -10th International Conference on Advanced Computational Intelligence, ICACI

Conference

Title10th International Conference on Advanced Computational Intelligence, ICACI 2018
PlaceChina
CityXiamen, Fujian
Period29 - 31 March 2018

Abstract

The portfolio optimization problem is a multi-objective problem which takes risk and return as optimization objectives. It is complicated in reality with many restrictions which results in an complex pareto front. MOEA/D is a popular multi-objective evolutionary algorithm framework with decomposition method, which has widely been used to solve multi-objective problems. In order to solve portfolio optimization problem with complex pareto front more effectively, we propose a new algorithm named MOEA/D-CP based on MOEA/D, which utilizes a new weight vector generation approach to generate a evenly distributed set of weight vectors. The experimental results show that the MOEA/D-CP performs much better than algorithm based on original MOEA/D.

Research Area(s)

  • Complex pareto front, Portfolio optimization, Weight vector generation

Citation Format(s)

A new evolutionary algorithm based on MOEA/D for portfolio optimization. / Zhang, Heng; Zhao, Yaoyu; Wang, Feng et al.
Proceedings of 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2018. p. 831-836 (Proceedings -10th International Conference on Advanced Computational Intelligence, ICACI ).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review