A Novel Algorithm for Global Optimization: Rat Swarm Optimizer

Dhiman, Gaurav and Garg, Meenakshi and Nagar, Atulya K. and Kumar, Vijay and Dehghani, Mohammad (2020) A Novel Algorithm for Global Optimization: Rat Swarm Optimizer. Journal of Ambient Intelligence and Humanized Computing. ISSN 1868-5137 (Accepted for Publication)

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Abstract

This paper presents a novel bio-inspired optimization algorithm called Rat Swarm Optimizer (RSO) for solving the challenging optimization problems. The main inspiration of this optimizer is the chasing and attacking behaviors of rats in nature. This paper mathematically models these behaviors and benchmarks on a set of 38 test problems to ensure its applicability on different regions of search space. The RSO algorithm is compared with eight well-known optimization algorithms to validate its performance. It is then employed on six real-life constrained engineering design problems. The convergence and computational analysis are also investigated to test exploration, exploitation, and local optima avoidance of proposed algorithm. The experimental results reveal that the proposed RSO algorithm is highly effective in solving real world optimization problems as compared to other well-known optimization algorithms.
Note that the source codes of the proposed technique are available at:
http://www.dhimangaurav.com

Item Type: Article
Additional Information and Comments: This is the author's version of an article that was accepted for publication in the Journal of Ambient Intelligence and Humanized Computing. When published, the final version will be available from https://www.springer.com/journal/12652/
Keywords: Optimization; Metaheuristics; Swarm-intelligence; Benchmark test functions; Engineering design problems.
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Atulya Nagar
Date Deposited: 13 Jul 2020 15:41
Last Modified: 13 Jul 2020 15:41
URI: https://hira.hope.ac.uk/id/eprint/3100

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