Quokka swarm optimization: A new nature-inspired metaheuristic optimization algorithm

Metaheuristics are efficient algorithms designed to address a broad spectrum of optimization challenges and offer satisfactory solutions, even in scenarios of limited processing capability or incomplete information. It has been observed that no single metaheuristic algorithm is universally ideal for...

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Bibliographic Details
Published in:Journal of Intelligent Systems
Main Authors: AL-kubaisy Wijdan Jaber, AL-Khateeb Belal
Format: Article
Language:English
Published: De Gruyter 2024-06-01
Subjects:
quokka swarm optimization
metaheuristic
swarm intelligence
evolutionary algorithms
particle swarm optimization
exploration and exploitation
Online Access:https://doi.org/10.1515/jisys-2024-0051
Description
Summary:Metaheuristics are efficient algorithms designed to address a broad spectrum of optimization challenges and offer satisfactory solutions, even in scenarios of limited processing capability or incomplete information. It has been observed that no single metaheuristic algorithm is universally ideal for all applications. This realization underscores the opportunity for the introduction of new metaheuristic algorithms or enhancements to existing ones.
ISSN:2191-026X

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