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.