A Modified iMOEA/D for Many-objective Optimization Problems with Complicated Pareto Fronts

Ghizlane Aboulbaroud, Driss Mentagui

2018

Abstract

In real life, multiobjective evolutionary algorithms have many areas of applications, such as intelligence transportations systems, management problems, data mining, data-analysis and so on. Due to the importance of these problems, researchers have investigated several approaches to deal with them. Decomposition is one of the basic strategies used in multiobjective evolutionary optimization. In this paper, a modified iMOEA/D evolutionary algorithm based decomposition is suggested. This proposition allows dealing with Many-objective optimization problems with complicated Pareto fronts. The performance of this algorithm is demonstrated using a set of benchmark problems in comparison with other recently proposed algorithms.

Paper Citation

in Harvard Style

Aboulbaroud G. and Mentagui D. (2018). A Modified iMOEA/D for Many-objective Optimization Problems with Complicated Pareto Fronts.In Proceedings of the 1st International Conference of Computer Science and Renewable Energies - Volume 1: ICCSRE, ISBN 978-989-758-431-2, pages 94-101. DOI: 10.5220/0009774000940101

in Bibtex Style

@conference{iccsre18,
author={Ghizlane Aboulbaroud and Driss Mentagui},
title={A Modified iMOEA/D for Many-objective Optimization Problems with Complicated Pareto Fronts},
booktitle={Proceedings of the 1st International Conference of Computer Science and Renewable Energies - Volume 1: ICCSRE,},
year={2018},
pages={94-101},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009774000940101},
isbn={978-989-758-431-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference of Computer Science and Renewable Energies - Volume 1: ICCSRE,
TI - A Modified iMOEA/D for Many-objective Optimization Problems with Complicated Pareto Fronts
SN - 978-989-758-431-2
AU - Aboulbaroud G.
AU - Mentagui D.
PY - 2018
SP - 94
EP - 101
DO - 10.5220/0009774000940101