Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F21%3A50018821" target="_blank" >RIV/62690094:18470/21:50018821 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/9638618" target="_blank" >https://ieeexplore.ieee.org/document/9638618</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2021.3133286" target="_blank" >10.1109/ACCESS.2021.3133286</a>

Result language

angličtina

Original language name

Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems

Original language description

Optimization algorithms are one of the effective stochastic methods in solving optimization problems. In this paper, a new swarm-based algorithm called Northern Goshawk Optimization (NGO) algorithm is presented that simulates the behavior of northern goshawk during prey hunting. This hunting strategy includes two phases of prey identification and the tail and chase process. The various steps of the proposed NGO algorithm are described and then its mathematical modeling is presented for use in solving optimization problems. The ability of NGO to solve optimization problems is evaluated on sixty-eight different objective functions. To analyze the quality of the results, the proposed NGO algorithm is compared with eight well-known algorithms, particle swarm optimization, genetic algorithm, teaching-learning based optimization, gravitational search algorithm, grey wolf optimizer, whale optimization algorithm, tunicate swarm algorithm, and marine predators algorithm. In addition, for further analysis, the proposed algorithm is also employed to solve four engineering design problems. The results of simulations and experiments show that the proposed NGO algorithm, by creating a proper balance between exploration and exploitation, has an effective performance in solving optimization problems and is much more competitive than similar algorithms.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Access

ISSN

2169-3536

e-ISSN

—

Volume of the periodical

9

Issue of the periodical within the volume

06.12.2021

Country of publishing house

US - UNITED STATES

Number of pages

22

Pages from-to

162059-162080

UT code for WoS article

000730458900001

EID of the result in the Scopus database

2-s2.0-85121349685