Abstract
Gravitational search algorithm (GSA) is a simple well known meta-heuristic search algorithm based on the law of gravity and the law of motion. In this article, a new variant of GSA is introduced, namely Exploitative Gravitational Search Algorithm (EGSA). In the proposed EGSA, two control parameters (Kbest and Gravitational constant) are modified that play an important role in GSA. Gravitation constant G is reduced iteratively to maintain a proper balance between exploration and exploitation of the search space. Further, To enhance the searching speed of algorithm Kbest (best individuals) is exponentially decreased. The performance of proposed algorithm is measured in term of reliability, robustness and accuracy through various statistical analyses over 12 complex test problems. To show the competitiveness of the proposed strategy, the reported results are compared with the results of GSA, Fitness Based Gravitational Search Algorithm (FBGSA) and Biogeography Based Optimization (BBO) algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bansal, J.C., Sharma, H., Arya, K.V., Deep, K., Pant, M.: Self-adaptive artificial bee colony. Optimization 63(10), 1513–1532 (2014)
Bansal, J.C., Sharma, H., Arya, K.V., Nagar, A.: Memetic search in artificial bee colony algorithm. Soft Comput. 17(10), 1911–1928 (2013)
Guo, Z.: A hybrid optimization algorithm based on artificial bee colony and gravitational search algorithm. Int. J. Digital Content Technol. Appl. 6(17) (2012)
Gupta, A., Sharma, N., Sharma, H.: Fitness based gravitational search algorithm. In: Proceedings of IEEE International Conference on Computing Communication and Automation. IEEE (Accepted 2016)
Holliday, D., Resnick, R., Walker, J.: Fundamentals of physics (1993)
Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: Gsa: a gravitational search algorithm. Inf. Sci. 179(13), 2232–2248 (2009)
Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: Bgsa: binary gravitational search algorithm. Nat. Comput. 9(3), 727–745 (2010)
Sarafrazi, S., Nezamabadi-Pour, H., Saryazdi, S.: Disruption: a new operator in gravitational search algorithm. Scientia Iranica 18(3), 539–548 (2011)
Sharma, K., Gupta, P.C., Sharma, H.: Fully informed artificial bee colony algorithm. J. Exp. Theor. Artif. Intell. 1–14 (2015)
Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)
Sudin, S., Nawawi, S.W., Faiz, A., Abidin, Z., Rahim, M.A.A., Khalil, K., Ibrahim, Z., Md Yusof, Z.: A modified gravitational search algorithm for discrete optimization problem
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gupta, A., Sharma, N., Sharma, H. (2017). Exploitative Gravitational Search Algorithm. In: Deep, K., et al. Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 546. Springer, Singapore. https://doi.org/10.1007/978-981-10-3322-3_15
Download citation
DOI: https://doi.org/10.1007/978-981-10-3322-3_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3321-6
Online ISBN: 978-981-10-3322-3
eBook Packages: EngineeringEngineering (R0)