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Authors: Ibtissem Bouoni 1 ; Nadia Smairi 2 and Kamel Zidi 3

Affiliations: 1 Faculty of Science Gafsa, Tunisia ; 2 ISG Tunis, Tunisia ; 3 University of Tabuk, Saudi Arabia

Keyword(s): Multi-objective Optimization, Particle Swarm Optimization, MO-TRIBES, Inheritance Technique, Approximation Technique, Fitness Evaluation, Time.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Evolutionary Computation and Control ; Health Engineering and Technology Applications ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge-Based Systems ; Optimization Algorithms ; Software Agents for Intelligent Control Systems ; Symbolic Systems

Abstract: In this paper, we propose to introduce inheritance and approximation techniques for the evaluation of the objective function. The main idea of the approaches is to reduce MO-TRIBES complexity. Besides, in our study, we incorporate at the beginning, an inheritance technique then an approximation technique (Approximation 1: to consider the whole swarm, Approximation 2: to consider the tribe) at the evaluation of the objective function. We conducted in our experiments eleven well-known multi-objective test functions. The results showed a good behavior of our propositions on most tested functions. Moreover, TRIBES-inheritance provided the best compared to MO-TRIBES, we concluded that MO-TRIBES with inheritance give the best time than MO-TRIBES and MO-TRIBES with approximation. It also kept the same performances with MO-TRIBES with a simple improvement for several functions.

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Paper citation in several formats:
Bouoni, I.; Smairi, N. and Zidi, K. (2015). Study of Inheritance and Approximation Techniques for Adaptive Multi-objective Particle Swarm Optimization. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-122-9; ISSN 2184-2809, SciTePress, pages 146-154. DOI: 10.5220/0005529901460154

@conference{icinco15,
author={Ibtissem Bouoni. and Nadia Smairi. and Kamel Zidi.},
title={Study of Inheritance and Approximation Techniques for Adaptive Multi-objective Particle Swarm Optimization},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2015},
pages={146-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005529901460154},
isbn={978-989-758-122-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Study of Inheritance and Approximation Techniques for Adaptive Multi-objective Particle Swarm Optimization
SN - 978-989-758-122-9
IS - 2184-2809
AU - Bouoni, I.
AU - Smairi, N.
AU - Zidi, K.
PY - 2015
SP - 146
EP - 154
DO - 10.5220/0005529901460154
PB - SciTePress