Study of inheritance and approximation techniques for adaptive multi-objective Particle Swarm Optimization

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 tech...

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Bibliographic Details
Published in2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO) Vol. 1; pp. 146 - 154
Main Authors Bouoni, Ibtissem, Smairi, Nadia, Zidi, Kamel
Format Conference Proceeding
LanguageEnglish
Published SCITEPRESS 01.07.2015
Subjects
Approximation algorithms
Approximation methods
Approximation Technique
Complexity theory
Fitness Evaluation
Inheritance Technique
Linear programming
MO-TRIBES
Multi-objective Optimization
Optimization
Particle swarm optimization
Time
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Summary: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.