Paper Info
Title
Gravitational Search Algorithm And Its Variants
Abstract
Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In GSA, a collection of objects interacts with each other under the Newtonian gravity and the laws of motion. The performances of objects are measured by masses. All these objects attract each other by the gravity force, while this force causes a global movement of all objects toward the objects with heavier masses. The position of the object corresponds to a solution of the problem. The positions of the objects are updated every iteration and the best fitness along with its corresponding object is stored. Heavier masses move slowly than lighter ones. The algorithm terminates after a specified number of iterations after which the best fitness becomes the global fitness for a particular problem and the positions of the corresponding object becomes the global solution of that problem. This paper presents a review of GSA and its variants.
Year
DOI
Venue
2016
10.1142/S0218001416390018
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Gravitational search algorithm, nature-inspired computing, gravitational kinematics, metaheuristic algorithm
Newton's laws of motion,Kinematics,Pattern recognition,Gravity force,Artificial intelligence,Newtonian fluid,Classical mechanics,Gravitational search algorithm,Gravitation,Mathematics
Journal
Volume
Issue
ISSN
30
8
0218-0014
Citations 
PageRank 
References 
6
0.39
40
Authors
2
Name
Order
Citations
PageRank
Nazmul H. Siddique112515.71
Hojjat Adeli22150148.37