An Experimental Analysis of Meta Heuristic Techniques on Unimodal and Multimodal Functions
Anju Bala1, Priti2
1Anju Bala, Research Scholar, Dept. of Computer Science and Applications, M.D.U, Rohtak, India.
2Priti, Assistant Professor, Dept. of Computer Science and Applications, M.D.U, Rohtak, India.
Manuscript received on 08 June 2019 | Revised Manuscript received on 13 June 2019 | Manuscript Published on 08 July 2019 | PP: 128-135 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H10350688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The advancement in the technology leads to the increase in the complexity of the problems. The traditional heuristic algorithms are not suitable for the optimized results of such complex problems. This leads to generation of Meta heuristic techniques which incorporate the exploration as well as the exploitation search. This paper studies different state of art Meta heuristic techniques like ant colony optimization, particle swarm optimization, differential evolution and genetic algorithm. This paper also covers different stable modified version of these techniques and implements the same to analyze the performance on different unimodal and the multimodal functions. The analysis clearly signifies the use of Meta heuristic techniques based on application.
Keywords: Exploration, Exploitation, Meta-heuristic, Multimodal and Unimodal
Scope of the Article: Algorithm Engineering