A modi ed variant of grey wolf optimizer

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SINGH N.

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Journal Paper

Paper Information

Journal: Scientia Iranica Year:2020 | Volume:27 | Issue:3 (Transactions D: Computer Science and Engineering and Electrical Engineering) Page(s): 1450-1466

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Information Journal Paper

Title

A modi ed variant of grey wolf optimizer

Author(s)

SINGH N. | Issue Writer Certificate

Keywords

Particle Swarm Optimization (PSO)

Grey Wolf Optimization (GWO)

Mean grey wolf optimization

Meta-heuristics

Abstract

The original version of Grey Wolf Optimization (GWO) algorithm has a few disadvantages such as low solving accuracy, unsatisfactory ability of local searching, and slow convergence rate. In order to compensate these disadvantages of grey wolf optimizer, a new version of grey wolf optimizer algorithm was proposed by modifying the encircling behavior and position update equations of GWO algorithm. The accuracy and convergence performances of the modi ed variant were tested on several well-known classical, sine datasets, and cantilever beam design functions. For veri cation, the results were compared with some of the most powerful, well-known algorithms, i. e., particle swarm optimization, grey wolf optimizer, and Mean grey wolf optimization. The experimental solutions demonstrated that the modi ed variant was able to provide very comparable solutions in terms of improved minimum value of objective function, maximum value of objective function, mean, standard deviation, and convergence rate.

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APA: Copy

SINGH, N.. (2020). A modi ed variant of grey wolf optimizer. SCIENTIA IRANICA, 27(3 (Transactions D: Computer Science and Engineering and Electrical Engineering)), 1450-1466. SID. https://sid.ir/paper/973731/en

Vancouver: Copy

SINGH N.. A modi ed variant of grey wolf optimizer. SCIENTIA IRANICA[Internet]. 2020;27(3 (Transactions D: Computer Science and Engineering and Electrical Engineering)):1450-1466. Available from: https://sid.ir/paper/973731/en

IEEE: Copy

N. SINGH, “A modi ed variant of grey wolf optimizer,” SCIENTIA IRANICA, vol. 27, no. 3 (Transactions D: Computer Science and Engineering and Electrical Engineering), pp. 1450–1466, 2020, [Online]. Available: https://sid.ir/paper/973731/en

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