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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/18964
Title: A New Improved Gravitational Search Algorithm for Function Optimization Using a Novel "best-So-Far" Update Mechanism
Authors: Singh A.
Deep K.
Nagar A.
Published in: Proceedings of 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015
Abstract: The focus of this paper is the memory-less Gravitational Search Algorithm (GSA), which is a unique nature inspired algorithms for continuous optimization, based on the laws of gravity and laws of motion. In order to improve the efficiency, reliability and robustness of GSA, an improved GSA is presented in this paper, which incorporates a simple update mechanism of "best-so-far" particle. The performance of Improved GSA and original GSA is well tested on a set of 7 scalable unimodal functions, 6 scalable multi modal functions and 10 non-scalable functions with varying difficulty levels. These 23 problems are the same problems which were presented in the original paper of GSA. Based on the extensive computational analysis it is shown that the improved GSA outperforms original GSA in terms of improved solution quality and faster convergence. © 2015 IEEE.
Citation: Proceedings of 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015, (2016), 35- 39
URI: https://doi.org/10.1109/ISCMI.2015.21
http://repository.iitr.ac.in/handle/123456789/18964
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Function Optimization
Gravitational Search Algorithm
Heuristic Technique
Algorithms
Artificial intelligence
Heuristic methods
Learning algorithms
Soft computing
Computational analysis
Continuous optimization
Function Optimization
Gravitational search algorithm (GSA)
Gravitational search algorithms
Heuristic techniques
Nature inspired algorithms
Reliability and robustness
Optimization
ISBN: 9780000000000
Author Scopus IDs: 57211750941
8561208900
8840681600
Author Affiliations: Singh, A., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttrakhand, 247667, India
Deep, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttrakhand, 247667, India
Nagar, A., Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, L16 9JD, United Kingdom
Funding Details: The first author would like to thank Council for Scientific and Industrial Research (CSIR), New Delhi, India, for providing him the financial support vide grant number 09/143(0824)/2012-EMR-I.
Appears in Collections:Conference Publications [MA]

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