A multi-strategy enhanced reptile search algorithm for global optimization and engineering optimization design problems DOI Creative Commons
Liping Zhou, Xu Liu,

Ruiqing Tian

et al.

Cluster Computing, Journal Year: 2024, Volume and Issue: 28(2)

Published: Dec. 5, 2024

The reptile search algorithm (RSA) is a well-known swarm-based metaheuristic inspired by the hunting behaviors of crocodiles. To overcome problems falling into local optima and premature convergence, this paper proposes multi-strategy enhanced (MRSA), which integrates novel dynamic evolutionary sense, prey approaching strategy Cauchy mutation strategy. comes from secretary bird optimization applied to strengthen exploration capability RSA. A comparative performance analysis conducted using CEC2005, CEC2017 CEC2022 benchmark functions. And fifteen algorithms are employed for comparison. results numerical, convergence curves, boxplots, Wilcoxon rank-sum test Friedman ranking confirm efficacy stability proposed MRSA, indicating its superior compared other algorithms. Moreover, seven practical engineering design tasks used MRSA in real-world problems. also show that can efficiently obtain better optimal solution existing methods.

Language: Английский

Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems DOI
Anas Bouaouda, Fatma A. Hashim, Yassine Sayouti

et al.

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: May 16, 2024

Language: Английский

Citations

33
An efficient adaptive-mutated Coati optimization algorithm for feature selection and global optimization DOI Creative Commons
Fatma A. Hashim, Essam H. Houssein, Reham R. Mostafa

et al.

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 85, P. 29 - 48

Published: Nov. 17, 2023

The feature selection (FS) problem has occupied a great interest of scientists lately since the highly dimensional datasets might have many redundant and irrelevant features. FS aims to eliminate such features select most important ones that affect classification performance. Metaheuristic algorithms are best choice solve this combinatorial problem. Recent researchers invented adapted new algorithms, hybridized or enhanced existing by adding some operators In our paper, we added Coati optimization algorithm (CoatiOA). first operator is adaptive s-best mutation enhance balance between exploration exploitation. second directional rule opens way discover search space thoroughly. final enhancement controlling direction toward global best. We tested proposed mCoatiOA in solving) solving challenging problems from CEC'20 test suite. performance was compared with Dandelion Optimizer (DO), African vultures (AVOA), Artificial gorilla troops optimizer (GTO), whale (WOA), Fick's Law Algorithm (FLA), Particle swarm (PSO), Harris hawks (HHO), Tunicate (TSA). According average fitness, it can be observed method, mCoatiOA, performs better than other on 8 functions. It lower standard deviation values competitive algorithms. Wilcoxon showed results obtained significantly different those rival been as algorithm. Fifteen benchmark various types were collected UCI machine-learning repository. Different evaluation criteria used determine effectiveness method. achieved comparison published methods. mean 75% datasets.

Language: Английский

Citations

34
An enhanced chameleon swarm algorithm for global optimization and multi-level thresholding medical image segmentation DOI
Reham R. Mostafa, Essam H. Houssein, Abdelazim G. Hussien

et al.

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(15), P. 8775 - 8823

Published: March 5, 2024

Language: Английский

Citations

14
Artificial hummingbird algorithm: Theory, variants, analysis, applications, and performance evaluation DOI
Buddhadev Sasmal, Arunita Das, Krishna Gopal Dhal

et al.

Computer Science Review, Journal Year: 2025, Volume and Issue: 56, P. 100727 - 100727

Published: Jan. 18, 2025

Language: Английский

Citations

1
Achieving Optimal PV Allocation in Distribution Networks Using a Modified Reptile Search Algorithm DOI Creative Commons
Salah Kamel, Hussein Abdel-Mawgoud, Fatma A. Hashim

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 42651 - 42666

Published: Jan. 1, 2024

As a result of advancements in technology and population growth, there has been significant rise global electrical demand. Consequently, the integration renewable sources such as photovoltaic (PV) systems into distribution gained popularity an effective solution to meet increasing load requirements. This research paper introduces optimized approach for allocating PV at various penetration levels, utilizing powerful optimization algorithm known modified Reptile Search Algorithm (MRSA). MRSA is enhanced version (RSA) that addresses issues related local optima stagnation premature convergence by incorporating disperse ambush strategy proportional selection method. To assess efficacy proposed optimizer, comprehensive set comparative experiments was conducted using CEC'2020 test suite. The experimental results consistently demonstrate suggested technique outperforms alternative methods terms both speed accuracy. Additionally, employed determine optimal allocation systems, with total power loss serving single objective function while considering equality inequality constraints. IEEE 33-bus RDS system. obtained provide evidence multiple yields superior outcomes compared system levels within RDS. Furthermore, integrating higher better than them lower levels.

Language: Английский

Citations

7
A CNN-based model to count the leaves of rosette plants (LC-Net) DOI Creative Commons

Mainak Deb,

Krishna Gopal Dhal, Arunita Das

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 17, 2024

Abstract Plant image analysis is a significant tool for plant phenotyping. Image has been used to assess trails, forecast growth, and offer geographical information about images. The area segmentation counting of the leaf major component phenotyping, which can be measure growth plant. Therefore, this paper developed convolutional neural network-based model called LC-Net. original segmented parts are fed as input because part provides additional proposed well-known SegNet utilised obtain it outperforms four other popular Convolutional Neural Network (CNN) models, namely DeepLab V3+, Fast FCN with Pyramid Scene Parsing (PSP), U-Net, Refine Net. LC-Net compared recent CNN-based models over combined Computer Vision Problems in Phenotyping (CVPPP) KOMATSUNA datasets. subjective numerical evaluations experimental results demonstrate superiority tested models.

Language: Английский

Citations

6
An enhanced exponential distribution optimizer and its application for multi-level medical image thresholding problems DOI Creative Commons
Fatma A. Hashim, Abdelazim G. Hussien, Anas Bouaouda

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 93, P. 142 - 188

Published: March 15, 2024

In this paper, an enhanced version of the Exponential Distribution Optimizer (EDO) called mEDO is introduced to tackle global optimization and multi-level image segmentation problems. EDO a math-inspired optimizer that has many limitations in handling complex multi-modal tries solve these drawbacks using 2 operators: phasor operator for diversity enhancement adaptive p-best mutation strategy preventing it converging local optima. To validate effectiveness suggested optimizer, comprehensive set comparative experiments CEC'2020 test suite was conducted. The experimental results consistently prove technique outperforms its counterparts terms both convergence speed accuracy. Moreover, algorithm applied multi-threshold method with Otsu's entropy, providing further evidence performance. evaluated by comparing those existing well-known algorithms at various threshold levels. proposed attains exceptional

Language: Английский

Citations

6
Boosting manta rays foraging optimizer by trigonometry operators: a case study on medical dataset DOI
Nabil Neggaz, Imène Neggaz, Mohamed Abd Elaziz

et al.

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(16), P. 9405 - 9436

Published: March 4, 2024

Language: Английский

Citations

5
A Comprehensive Survey on African Vulture Optimization Algorithm DOI
Buddhadev Sasmal, Arunita Das, Krishna Gopal Dhal

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 31(3), P. 1659 - 1700

Published: Nov. 30, 2023

Language: Английский

Citations

13
AEOWOA: hybridizing whale optimization algorithm with artificial ecosystem-based optimization for optimal feature selection and global optimization DOI
Reham R. Mostafa, Abdelazim G. Hussien,

Marwa A. Gaheen

et al.

Evolving Systems, Journal Year: 2024, Volume and Issue: 15(5), P. 1753 - 1785

Published: May 15, 2024

Language: Английский

Citations

4