MGCHMO: A dynamic differential human memory optimization with Cauchy and Gauss mutation for solving engineering problems DOI

Jialing Yan,

Gang Hu,

Bin Shu

et al.

Advances in Engineering Software, Journal Year: 2024, Volume and Issue: 198, P. 103793 - 103793

Published: Oct. 22, 2024

Language: Английский

Dynamic Agricultural Pest Classification Using Enhanced SAO-CNN and Swarm Intelligence Optimization for UAVs DOI Creative Commons
Shiwei Chu,

Wenxia Bao

International Journal of Cognitive Computing in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
mESC: An Enhanced Escape Algorithm Fusing Multiple Strategies for Engineering Optimization DOI Creative Commons
Jia Liu,

Jianwei Yang,

Lele Cui

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 232 - 232

Published: April 8, 2025

A multi-strategy enhanced version of the escape algorithm (mESC, for short) is proposed to address challenges balancing exploration and development stages low convergence accuracy in (ESC). Firstly, an adaptive perturbation factor strategy was employed maintain population diversity. Secondly, introducing a restart mechanism enhance capability mESC. Finally, dynamic centroid reverse learning designed balance local development. In addition, order accelerate global speed, boundary adjustment based on elite pool proposed, which selects individuals replace bad individuals. Comparing mESC with latest metaheuristic high-performance winner CEC2022 testing suite, numerical results confirmed that outperforms other competitors. superiority handling problems verified through several classic real-world optimization problems.

Language: Английский

Citations

0
Snake Optimization Algorithm Augmented by Adaptive t-Distribution Mixed Mutation and Its Application in Energy Storage System Capacity Optimization DOI Creative Commons
Yinggao Yue, Li Cao,

Changzu Chen

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 244 - 244

Published: April 16, 2025

To address the drawbacks of traditional snake optimization method, such as a random population initialization, slow convergence speed, and low accuracy, an adaptive t-distribution mixed mutation strategy is proposed. Initially, Tent-based chaotic mapping quasi-reverse learning approach are utilized to enhance quality initial solution initialization process original method. During evolution stage, novel foraging introduced substitute stage This perturbs mutates at optimal position generate new solutions, thereby improving algorithm’s ability escape local optima. The mating mode in replaced with opposite-sex attraction mechanism, providing algorithm more opportunities for global exploration exploitation. improved method accelerates improves accuracy while balancing exploitation capabilities. experimental results demonstrate that outperforms other methods, including standard technique, terms robustness accuracy. Additionally, each improvement technique complements amplifies effects others.

Language: Английский

Citations

0
GSRPSO: A multi-strategy integrated particle swarm algorithm for multi-threshold segmentation of real cervical cancer images DOI
Gang Hu,

Yixuan Zheng,

Essam H. Houssein

et al.

Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 91, P. 101766 - 101766

Published: Oct. 31, 2024

Language: Английский

Citations

3
Multi-strategy improved seagull optimization algorithm and its application in practical engineering DOI
Peng Chen, Huilin Li, Feng He

et al.

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: July 24, 2024

Metaheuristic algorithms play a crucial role in engineering optimization, as they can find the optimal parameter configuration systems. This article proposes multi-strategy improved seagull optimization algorithm (OPSOA) to solve application problems. Aiming problems of slow search speed and low convergence accuracy standard (SOA), four strategies, including Lévy flight Cauchy mutation, were introduced improve its performance. Comparison shows that OPSOA incomplete are better than SOA, indicating each improvement is effective. By testing benchmark functions CEC 2017 2022, it shown has strong ability solution superior other terms speed. The this practical proves significant advantages solving complex

Language: Английский

Citations

2
MAHACO: Multi-algorithm hybrid ant colony optimizer for 3D path planning of a group of UAVs DOI
Gang Hu, Feiyang Huang, Bin Shu

et al.

Information Sciences, Journal Year: 2024, Volume and Issue: unknown, P. 121714 - 121714

Published: Nov. 1, 2024

Language: Английский

Citations

2
DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications DOI
Gang Hu,

Changsheng Gong,

Bin Shu

et al.

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2024, Volume and Issue: 431, P. 117251 - 117251

Published: Aug. 16, 2024

Language: Английский

Citations

1
A hybrid sparrow optimization Kriging model and its application in geological modeling DOI Creative Commons
Xiaonan Shi,

Y B Wang,

Hsien Tang Wu

et al.

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

Published: Oct. 19, 2024

Language: Английский

Citations

1
DMT-OMPA: Innovative applications of an efficient adversarial Marine Predators Algorithm based on dynamic matrix transformation in engineering design optimization DOI
Z. Zhang, Shu‐Chuan Chu, Trong-The Nguyen

et al.

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2024, Volume and Issue: 431, P. 117247 - 117247

Published: July 29, 2024

Language: Английский

Citations

0
MGCHMO: A dynamic differential human memory optimization with Cauchy and Gauss mutation for solving engineering problems DOI

Jialing Yan,

Gang Hu,

Bin Shu

et al.

Advances in Engineering Software, Journal Year: 2024, Volume and Issue: 198, P. 103793 - 103793

Published: Oct. 22, 2024

Language: Английский

Citations

0