Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes

Author

Zhao, Shi-Zheng ; Suganthan, Ponnuthurai Nagaratnam ; Zhang, Qingfu

Author_Institution

Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore

Volume

16

Issue

3

fYear

2012

fDate

6/1/2012 12:00:00 AM

Firstpage

442

Lastpage

446

Abstract

The multiobjective evolutionary algorithm based on decomposition (MOEA/D) has demonstrated superior performance by winning the multiobjective optimization algorithm competition at the CEC 2009. For effective performance of MOEA/D, neighborhood size (NS) parameter has to be tuned. In this letter, an ensemble of different NSs with online self-adaptation is proposed (ENS-MOEA/D) to overcome this shortcoming. Our experimental results on the CEC 2009 competition test instances show that an ensemble of different NSs with online self-adaptation yields superior performance over implementations with only one fixed NS.

Keywords

evolutionary computation; decomposition-based multiobjective evolutionary algorithm; multiobjective optimization algorithm competition; neighborhood sizes; online self-adaptation; Approximation algorithms; Educational institutions; Evolutionary computation; Heuristic algorithms; Pareto optimization; Vectors; Decomposition; multiobjective optimization; self-adaptation;

fLanguage

English

Journal_Title

Evolutionary Computation, IEEE Transactions on

Publisher

ieee

ISSN

1089-778X

Type

jour

DOI

10.1109/TEVC.2011.2166159

Filename

6151117