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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/9936
Title: An efficient opposition based Lévy Flight Antlion optimizer for optimization problems
Authors: Dinkar S.K.
Deep, K.
Published in: Journal of Computational Science
Abstract: This work proposes a new efficient version of recently proposed Antlion Optimizer (ALO) namely Opposition based Lévy Flight Antlion optimizer (OB-LF-ALO). The upgraded version is conceptualized on the theory of Opposition based learning integrated with Lévy Flight for random walk in place of uniform distributed random walk in original ALO. The success of any optimization algorithm relies on adequate balancing of exploration and exploitation during the process of evolution. The original algorithm is prone to stagnate in local optima and requires diversified exploration with appropriate blending of exploitation. The proposed technique is well capable of accelerating convergence by enhancing the initial diversification and good exploitation capability at later stage of generations. The performance of developed algorithm is validated by applying a wide-ranging set of 27 unconstrained continuous benchmark test functions. The impact of generated random numbers after employing lévy flight and updated population after applying opposition based learning during evolution is analysed using certain metrics such as trajectories, elite convergence curve, average of absolute distance between search agents before and after improving the algorithm and data distribution using box plot diagrams. A non-parametric Wilcoxon ranksum test is used to exhibit its statistical significance. The projected algorithm is also compared with its recently developed version namely opposition based laplacian antlion optimizer (OB-L-ALO). The algorithm is also established with wide range of real life classical engineering optimization problem including two unconstrained and two constrained problems. The experimental analysis establishes that the developed variant OB-LF-ALO is superior as compared to ALO and OB-L-ALO. © 2018 Elsevier B.V.
Citation: Journal of Computational Science (2018), 29(): 119-141
URI: https://doi.org/10.1016/j.jocs.2018.10.002
http://repository.iitr.ac.in/handle/123456789/9936
Issue Date: 2018
Publisher: Elsevier B.V.
Keywords: Antlion optimizer
Lévy flight
Opposition based learning
ISSN: 18777503
Author Scopus IDs: 57196220500
8561208900
Author Affiliations: Dinkar, S.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
Funding Details: The first author is thankful to All India Council for Technical Education (AICTE), Government of India for funding this research. Mr. Shail K Dinkar is a Research Scholar at Department of Mathematics,IIT Roorkee, India. He has obtained MTech(Information Technology) from Guru Gobind Singh Indraprastha University, Delhi, India, Master of Computer Application(MCA)from U P Tech University, Lucknow, India and Bachelor of Science from C.C.S. University, Meerut, India. He has obtained national scholarship for earning maximum marks in whole district at 10th standard. He has more than 13 years of teaching experience in the field of Computer Application and Information Technology. He is pursuing pH.D. under the supervision of Prof. Kusum Deep. He is life member of Soft Computing Research Society(SCRS). His research area includes Nature Inspired Optimization techniques such as Antlion Optimizer, Particle Swarm Optimization and Genetic Algorithm etc. Dr. Kusum Deep is a Professor, with the Department of Mathematics, Indian Institute of Technology Roorkee, India. Born on August 15, 1958, she pursued B.Sc. Hons. and M.Sc. Hons. School from Centre for Advanced Studies, Panjab University, Chandigarh. An M.Phil. Gold Medallist, she earned her pH.D. from IIT Roorkee in 1988. She was awarded UGC National Merit Scholarship and UGC National Education Test Scholarship. She carried out research at Loughborough University, UK during 1993–94, under an International Post Doctorate Bursary funded by Commission of European Communities, Brussels. Fifteen students have been awarded PhD under her supervision and four are in progress. She has more than 100 research publications in refereed International Journals and more than 77 research papers in International/National Conferences. She is on the editorial board of a number of International and National Journals. She is a Senior Member of Operations Research Society of India, IEEE, Computer Society of India, Indian Mathematical Society and Indian Society of Industrial Mathematics. She is on the Expert Panel of the Department of Science and Technology, Govt. of India. Dr. Deep is having International Collaboration with Liverpool Hope University, Liverpool, UK and Korea University, Korea. Her research interests include Numerical Optimization, Evolutionary Algorithms, Genetic Algorithms, Particle Swarm Optimization, etc.
Corresponding Author: Deep, K.; Department of Mathematics, Indian Institute of Technology RoorkeeIndia; email: kusumfma@iitr.ac.in
Appears in Collections:Journal Publications [MA]

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