A Particle Swarm and Smell Agent-Based Hybrid Algorithm for Enhanced Optimization

A Particle Swarm and Smell Agent-Based Hybrid Algorithm for Enhanced Optimization

The particle swarm optimization (PSO) algorithm is widely used for optimization purposes across various domains, such as in precision agriculture, vehicular ad hoc networks, path planning, and for the assessment of mathematical test functions towards benchmarking different optimization algorithms. H...

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Bibliographic Details
Main Authors: Abdullahi T. Sulaiman, Habeeb Bello-Salau, Adeiza J. Onumanyi, Muhammed B. Mu’azu, Emmanuel A. Adedokun, Ahmed T. Salawudeen, Abdulfatai D. Adekale
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Algorithms
Subjects:
benchmark
optimal
particle swarm optimization
smell agent optimization
solution
test functions
Online Access:https://www.mdpi.com/1999-4893/17/2/53

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