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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10298
Title: Improving the Local Search Ability of Spider Monkey Optimization Algorithm Using Quadratic Approximation for Unconstrained Optimization
Authors: Gupta K.
Deep, K.
Bansal J.C.
Published in: Computational Intelligence
Abstract: Spider monkey optimization (SMO) algorithm, which simulates the food searching behavior of a swarm of spider monkeys, is a new addition to the class of swarm intelligent techniques for solving unconstrained optimization problems. The purpose of this article is to study the performance of SMO after incorporating quadratic approximation (QA) operator in it. The proposed version is named as QA-based spider monkey optimization (QASMO). An experimental study has been carried out to check the validity and applicability of QASMO. For validation purpose, the performance of QASMO is tested over a benchmark set of 46 scalable and nonscalable problems, and results are compared with the original SMO algorithm. In order to test the applicability of the proposed algorithm in solving real-life optimization problems, one of the most challenging optimization problems, namely, Lennard–Jones (LJ) problem is considered. LJ clusters containing atoms from three to ten have been taken into consideration, and results are presented. To the best of our knowledge, this is the first attempt to apply SMO and its proposed variant on a real-life problem. The results demonstrate that incorporation of QA in SMO has positive effects on its performance in terms of reliability, efficiency, and accuracy. ©2016 Wiley Periodicals, Inc.
Citation: Computational Intelligence (2017), 33(2): 210-240
URI: https://doi.org/10.1111/coin.12081
http://repository.iitr.ac.in/handle/123456789/10298
Issue Date: 2017
Publisher: Blackwell Publishing Inc.
Keywords: Lennard–Jones problem
spider monkey optimization, quadratic approximation, swarm intelligent techniques, unconstrained optimization, global optimization
ISSN: 8247935
Author Scopus IDs: 56954165300
8561208900
57189656835
Author Affiliations: Gupta, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Deep, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Bansal, J.C., Department of Applied Mathematics, South Asian UniversityAkbar Bhawan, Chankyapuri, New Delhi, India
Funding Details: The first author would like to acknowledge the Ministry of Human Resource Development, Government of India, for the financial support and the anonymous reviewers for their valuable comments and suggestions.
Corresponding Author: Gupta, K.; Department of Mathematics, Indian Institute of Technology RoorkeeIndia; email: gupta.kavita3043@gmail.com
Appears in Collections:Journal Publications [MA]

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