A Multi-objective Gravitational Search Algorithm

Recently there has been a great research conducted on diverse variations of multi-objective swarm optimization algorithms each of which might have its own strengths and weaknesses. Due to the high complexity of multi-objective problems the efficiency of these methods has become a matter of concern....

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Bibliographic Details
Published in:2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks pp. 7 - 12
Main Authors: Hassanzadeh, Hamid Reza, Rouhani, Modjtaba
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2010
Subjects:
Codes
Extraterrestrial measurements
Genetic algorithms
Gravity
Indexes
Indirect Niching
Linear programming
Metaheuristics
Multi-objective Gravitational Search Algorithm (MOGSA)
Multi-objective Particle Swarm Optimization (MOPSO)
Pareto Optimality
Particle swarm optimization
Search problems
Vectors
ISBN:1424478375, 9781424478378
Online Access:Get full text
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Summary:Recently there has been a great research conducted on diverse variations of multi-objective swarm optimization algorithms each of which might have its own strengths and weaknesses. Due to the high complexity of multi-objective problems the efficiency of these methods has become a matter of concern. In this paper a new multi-objective meta-heuristic algorithm based on gravitational forces is proposed and applied to different test benches. The acquired results proved the superiority of the algorithm comparing with other pioneering techniques such as the MOPSO
ISBN:1424478375
9781424478378
DOI:10.1109/CICSyN.2010.32