Paper Info
Title
A New Evolutionary Algorithm Based On Moea/D For Portfolio Optimization
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.
Year
Venue
Keywords
2018
PROCEEDINGS OF 2018 TENTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI)
portfolio optimization, weight vector generation, complex pareto front
Field
DocType
Citations 
Mathematical optimization,Evolutionary algorithm,Computer science,Weight,Multi-objective optimization,Decomposition method (constraint satisfaction),Portfolio optimization
Conference
1
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Heng Zhang18728.05
Yaoyu Zhao240.71
Feng Wang319519.03
Anran Zhang411.35
Pengwei Yang510.34
Aaron X. L. Shen622116.98