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International Transactions on Evolutionary and Metaheuristic Algorithms
Vol. 4, No. 2, Jun. 2018
State-of-the-Art Nature-inspired Metaheuristic Algorithms for Optimization Problems | Miscellaneous
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a Seemanta Engg College, Udala, India
Dr. Harihar Kalia
 orcid.org/0000-0001-7289-761X
 Corresponding Author
 Affiliation: Seemanta Engg College, Udala, India
 Tel: 9776032990
Phone: 9437238248  E-mail: smarahari07@gmail.com
2nd e-mail: hariharkalia@seemantaengg.ac.in  Biography: Harihar Kalia is an Assistant Professor in the Department of Computer Science and Engineering, Seemanta Engineering College, Jharpokharia, Mayurbhanj, Odisha. He received his M.Sc. degree in Mathematics from Ravenshaw University, Odisha in 1995, and the M.Tech degree in Computer Science from Utkal University, Vani Vihar, Odisha in 2002. He completed his PhD work in the area of Multi-Objective Fuzzy Rule Mining in Department Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore, Odisha, in 2015. His area of interest includes: Data Mining, Multi-Objective Optimization, Fuzzy Logic, Evolutionary Algorithms, and Hybrid Systems. He has about 19 years teaching experience, in teaching both graduate and postgraduate students. He is a member of Editorial and Reviewer Board in International Journal of Rough Computing and Intelligent Systems (IJRCIS), Reviewer in International Journal of Uncertainty, Fuzziness and Knowledge Based Systems (World Scientific) and Reviewer in International Journal of Applied Meta heuristic Computing (IJAMC), IGI Global.
Dr. Harihar Kalia's publications in ICSES
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This article has been retracted by International Computer Science and Engineering Society (ICSES) because of ethical misconduct, scientific distortion, or administrative error, and cannot be downloaded and used for any purpose based on the violation in ICSES Ethics in Publicationcall_made |
Retraction Note by the Editor-in-Chief
Highlights and Novelties
1. This is an editorial document for the journal by the editor.
2. To give a brief introduction about some state-of-the-art nature-inspired metaheuristic algorithms for optimization problems.
3. This editorial document highlights some purposes and objectives of our journal, ITEMA.
Manuscript Abstract
Nature-inspired metaheuristic algorithms are proved approaches for solving real-world complex optimization problems. Numerous works have been conducted on the development of metaheuristic optimization algorithms since the introduction of evolutionary algorithms. Almost all of these algorithms are inspired by biological phenomenon and are imitating the best characteristic in nature, which makes them powerful. As an example, genetic algorithm features crossover, mutation and selection operators simulating the biological evolution process. Particle Swarm Optimization (PSO), Cuckoo Search (CS) algorithm, Firefly Algorithm (FA), Bat Algorithm (BA), Harmony Search (HS), Ant Colony Optimization (ACO) etc. are of some well-known nature-inspired metaheuristic algorithms in the community. Laying Chicken Algorithm (LCA), Lion Optimization Algorithms (LOA) and Elephant Herding Optimization (EHO) are some recent developed algorithms. The flexibility and adaptability make these nature-inspired met heuristics algorithms popular among the research community. In this Editorial document, we present a state-of-the-Art of nature-inspired meta-heuristics algorithms for optimization problems.
Keywords
Nature-inspired algorithms metaheuristics optimization problems metaheuristics algorithms
Copyright and Licence
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. This manuscript is published in Open-Access manner based on the copyright licence of Creative Commons Attribution Non Commercial 4.0 International (CC BY-NC 4.0).
Cite this manuscript as
Harihar Kalia, "State-of-the-Art Nature-inspired Metaheuristic Algorithms for Optimization Problems ," International Transactions on Evolutionary and Metaheuristic Algorithms, vol. 4, no. 2, pp. 1-2, Jun. 2018.
For External Scientific Databeses
--BibTex--
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title="State-of-the-Art Nature-inspired Metaheuristic Algorithms for Optimization Problems ",
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journal="International Transactions on Evolutionary and Metaheuristic Algorithms (ITEMA)",
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number="2",
pages="1-2",
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publisher= "International Computer Science and Engineering Society (ICSES)",
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