Gradient-based optimizer: analysis and application of the Berry software product DOI
Laith Abualigah,

Laith Elkhalaifa,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 221 - 229

Published: Jan. 1, 2024

Language: Английский

Modified crayfish optimization algorithm for solving multiple engineering application problems DOI Creative Commons
Heming Jia,

Xuelian Zhou,

Jinrui Zhang

et al.

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(5)

Published: April 24, 2024

Abstract Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in later stage of algorithm, algorithm fall into local optimum. To solve these problems, this paper proposes an modified optimization (MCOA). Based on survival habits crayfish, MCOA environmental renewal mechanism that uses water quality factors guide seek a better environment. In addition, integrating learning strategy based ghost antagonism enhances its ability evade optimality. evaluate performance MCOA, tests were performed using IEEE CEC2020 benchmark function experiments conducted four constraint engineering problems feature selection problems. For constrained improved by 11.16%, 1.46%, 0.08% 0.24%, respectively, compared with COA. average fitness value accuracy are 55.23% 10.85%, respectively. shows solving complex spatial practical application The combination environment updating significantly improves MCOA. This discovery has important implications for development field optimization. Graphical

Language: Английский

Citations

34
Guided learning strategy: A novel update mechanism for metaheuristic algorithms design and improvement DOI
Heming Jia,

Chenghao Lu

Knowledge-Based Systems, Journal Year: 2024, Volume and Issue: 286, P. 111402 - 111402

Published: Jan. 13, 2024

Language: Английский

Citations

24
Particle swarm optimization algorithm: review and applications DOI
Laith Abualigah,

Ahlam Sheikhan,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 1, 2024

Language: Английский

Citations

15
Whale optimization algorithm: analysis and full survey DOI
Laith Abualigah,

Roa’a Abualigah,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 105 - 115

Published: Jan. 1, 2024

Language: Английский

Citations

12
Quantum approximate optimization algorithm: a review study and problems DOI
Laith Abualigah,

Saif AlNajdawi,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 147 - 165

Published: Jan. 1, 2024

Language: Английский

Citations

9
A review of mothflame optimization algorithm: analysis and applications DOI
Laith Abualigah,

Laheeb Al-Abadi,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 205 - 219

Published: Jan. 1, 2024

Language: Английский

Citations

9
Spider monkey optimizations: application review and results DOI
Laith Abualigah,

Sahar M. Alshatti,

Abiodun M. Ikotun

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 117 - 131

Published: Jan. 1, 2024

Language: Английский

Citations

9
Memory backtracking strategy: An evolutionary updating mechanism for meta-heuristic algorithms DOI
Heming Jia,

Chenghao Lu,

Zhikai Xing

et al.

Swarm and Evolutionary Computation, Journal Year: 2023, Volume and Issue: 84, P. 101456 - 101456

Published: Dec. 27, 2023

Language: Английский

Citations

21
Synergistic Swarm Optimization Algorithm DOI Open Access

Sharaf Alzoubi,

Laith Abualigah,

Mohamed Sharaf

et al.

Computer Modeling in Engineering & Sciences, Journal Year: 2023, Volume and Issue: 139(3), P. 2557 - 2604

Published: Dec. 26, 2023

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA).The SSOA combines principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently.A mechanism is employed, where particles exchange information learn from each other improve their behaviors.This enhances exploitation promising regions in space while maintaining exploration capabilities.Furthermore, adaptive mechanisms, such as dynamic parameter adjustment diversification strategies, are incorporated balance exploitation.By leveraging collaborative nature integrating cooperation, aims achieve superior convergence speed solution quality performance compared algorithms.The effectiveness proposed investigated solving 23 benchmark functions various engineering design problems.The experimental results highlight potential addressing challenging problems, making it tool wide range applications beyond.Matlab codes available at: https://www.mathworks.com/matlabcentral/fileexchange/153466-synergistic

Language: Английский

Citations

17
A review of Henry gas solubility optimization algorithm: a robust optimizer and applications DOI
Laith Abualigah,

Ghada Al-Hilo,

Ali Raza

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 177 - 192

Published: Jan. 1, 2024

Language: Английский

Citations

7