A novel version of whale optimization algorithm for solving optimization problems

Nima Khodadadi; El Sayed M. El-kenawy; Sepehr Faridmarandi; Mansoureh Shahabi Ghahfarokhi; Abdelhameed Ibrahim; Seyedali Mirjalili

doi:10.1016/B978-0-32-395365-8.00048-8

A novel version of whale optimization algorithm for solving optimization problems

Nima Khodadadi, El Sayed M. El-kenawy, Sepehr Faridmarandi, Mansoureh Shahabi Ghahfarokhi, Abdelhameed Ibrahim, Seyedali Mirjalili

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The hunting behavior of humpback whales served as the basis for developing a previously invented swarm-based optimization algorithm known as the whale optimization algorithm (WOA). To achieve more precise solutions with higher reliability and faster convergence, this research endeavors to improve upon the initial WOA formulation. The new technique, called the advanced whale optimization algorithm (AWOA), is put to the test in engineering optimization problems. The AWOA, along with other metaheuristic techniques presented in previous literature, was tested in four optimization problems. Based on the numerical results, it was concluded that the AWOA was more efficient compared to the WOA.

Original language	English
Title of host publication	Handbook of Whale Optimization Algorithm
Subtitle of host publication	Variants, Hybrids, Improvements, and Applications
Publisher	Elsevier
Pages	591-600
Number of pages	10
ISBN (Electronic)	9780323953658
ISBN (Print)	9780323953641
DOIs	https://doi.org/10.1016/B978-0-32-395365-8.00048-8
Publication status	Published - 1 Jan 2023

Keywords

Advanced whale optimization algorithm
Engineering problems
Optimization
Whale optimization algorithm

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10.1016/B978-0-32-395365-8.00048-8

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abstract = "The hunting behavior of humpback whales served as the basis for developing a previously invented swarm-based optimization algorithm known as the whale optimization algorithm (WOA). To achieve more precise solutions with higher reliability and faster convergence, this research endeavors to improve upon the initial WOA formulation. The new technique, called the advanced whale optimization algorithm (AWOA), is put to the test in engineering optimization problems. The AWOA, along with other metaheuristic techniques presented in previous literature, was tested in four optimization problems. Based on the numerical results, it was concluded that the AWOA was more efficient compared to the WOA.",

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AU - Khodadadi, Nima

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AU - Ghahfarokhi, Mansoureh Shahabi

AU - Ibrahim, Abdelhameed

AU - Mirjalili, Seyedali

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A novel version of whale optimization algorithm for solving optimization problems

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