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Review: Metaheuristic Optimization Algorithms

by Nader Behdad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 30
Year of Publication: 2022
Authors: Nader Behdad
10.5120/ijca2022922368

Nader Behdad . Review: Metaheuristic Optimization Algorithms. International Journal of Computer Applications. 184, 30 ( Oct 2022), 33-38. DOI=10.5120/ijca2022922368

@article{ 10.5120/ijca2022922368,
author = { Nader Behdad },
title = { Review: Metaheuristic Optimization Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2022 },
volume = { 184 },
number = { 30 },
month = { Oct },
year = { 2022 },
issn = { 0975-8887 },
pages = { 33-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number30/32506-2022922368/ },
doi = { 10.5120/ijca2022922368 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:22:49.150297+05:30
%A Nader Behdad
%T Review: Metaheuristic Optimization Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 30
%P 33-38
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial neural networks are used in a wide range of machine techniques that deal with it. Hundreds of well-known optimization algorithms are now easy to use, and essential scientific code libraries offer dozens of technologies. Given the problems of optimization, it can be hard to decide what methods to use. Optimization is making a function's output depending on its input parameters or arguments in the best way possible. Optimization is getting the most significant or minor value for an objective function from a set of inputs. Continuous function optimization is often used in machines where the information to processes, such as floating-point values, are numbered. The function gives back the parameter's value in real life. Combined optimization problems with discrete variables can be distinguished using continuous function optimization. To find the best solution for problems with continuous functions, different techniques can be used to solve, organize, and call them.

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Index Terms

Computer Science
Information Sciences

Keywords

Optimization Metaheuristic Algorithms

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