A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems

Alexey Vakhnin, Evgenii Sopov

2018

Abstract

Large-scale global optimization (LSGO) is known as one of the most challenging problem for evolutionary algorithms (EA). In this study, we have proposed a novel method of grouping variables for the cooperative coevolution (CC) framework (random adaptive grouping (RAG))). We have implemented the proposed approach in a new evolutionary algorithm (DECC-RAG), which uses the Self-adaptive Differential Evolution (DE) with Neighborhood Search (SaNSDE) as the core search technique. The RAG method is based on the following idea: after some predefined number of fitness evaluations in cooperative coevolution, a half of subcomponents with the worst fitness values randomly mixes indices of variables, and the corresponding evolutionary algorithms reset adaptation of parameters. We have evaluated the performance of the DECC-RAG algorithm with the large-scale global optimization (LSGO) benchmark problems proposed within the IEEE CEC 2010. The results of numerical experiments are presented and discussed. The results have shown that the proposed algorithm outperforms some popular LSGO approaches.

Paper Citation

in Harvard Style

Vakhnin A. (2018). A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems.In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-321-6, pages 261-268. DOI: 10.5220/0006903102610268

in Bibtex Style

@conference{icinco18,
author={Alexey Vakhnin},
title={A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2018},
pages={261-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006903102610268},
isbn={978-989-758-321-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - A Novel Method for Grouping Variables in Cooperative Coevolution for Large-scale Global Optimization Problems
SN - 978-989-758-321-6
AU - Vakhnin A.
PY - 2018
SP - 261
EP - 268
DO - 10.5220/0006903102610268