A Novel Hybrid Improved RIME Algorithm for Global Optimization Problems DOI Creative Commons

Wuke Li,

Xiong Yang,

Yuchen Yin

et al.

Biomimetics, Journal Year: 2024, Volume and Issue: 10(1), P. 14 - 14

Published: Dec. 31, 2024

The RIME algorithm is a novel physical-based meta-heuristic with strong ability to solve global optimization problems and address challenges in engineering applications. It implements exploration exploitation behaviors by constructing rime-ice growth process. However, comes couple of disadvantages: limited exploratory capability, slow convergence, inherent asymmetry between exploitation. An improved version more efficiency adaptability these issues now the form Hybrid Estimation Rime-ice Optimization, short, HERIME. A probabilistic model-based sampling approach estimated distribution utilized enhance quality population boost its capability. roulette-based fitness distance balanced selection strategy used strengthen hard-rime phase effectively balance phases We validate HERIME using 41 functions from IEEE CEC2017 CEC2022 test suites compare accuracy, stability four classical recent metaheuristic algorithms as well five advanced reveal fact that proposed outperforms all them. Statistical research Friedman Wilcoxon rank sum also confirms excellent performance. Moreover, ablation experiments effectiveness each individually. Thus, experimental results show has better search accuracy effective dealing problems.

Language: Английский

Reinforcement learning guided auto-select optimization algorithm for feature selection DOI
Hongbo Zhang, Xiaofeng Yue,

Xueliang Gao

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: 268, P. 126320 - 126320

Published: Jan. 5, 2025

Language: Английский

Citations

1
Efficient Adaptive Learning Rate for Convolutional Neural Network Based on Quadratic Interpolation Egret Swarm Optimization Algorithm DOI Creative Commons
Peiyang Wei, Mingsheng Shang,

Jiesan Zhou

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(18), P. e37814 - e37814

Published: Sept. 1, 2024

Language: Английский

Citations

6
V-shaped and S-shaped binary artificial protozoa optimizer (APO) algorithm for wrapper feature selection on biological data DOI Creative Commons
Amir Seyyedabbasi, Gang Hu, Hisham A. Shehadeh

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(3)

Published: Jan. 21, 2025

Language: Английский

Citations

0
A Track Segment Association Method Based on Heuristic Optimization Algorithm and Multistage Discrimination DOI Creative Commons
Yiming Chen, Zhikun Zhang, Hui Zhang

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 500 - 500

Published: Jan. 31, 2025

The fragmentation of vessel tracks represents a significant challenge in the context high-frequency surface wave radar (HFSWR) tracking. This paper proposes new track segment association (TSA) algorithm that integrates optimal tracklet assignment, iterative discrimination, and multi-stage association. reformulates assignment task as an state search problem for modeling solution purposes. To determine whether competing old tracklets can be associated, we assume existence public correlation between tracklets. However, due to fragmentation, this remains unknown. We need all candidate pairs within feasible parameter space, using fitness function value evaluation criterion. match are considered optimally associated. Since process involves searching across multiple dimensions, it constitutes high-dimensional optimization problem. accomplish task, catch fish (CFOA) is employed its ability escape local optima handle optimization, enhancing reliability assignment. Furthermore, achieve precise one-to-one associations by assigning through method proposed, abbreviate AN2O, inverse process, which assigns tracklet, abbreviated AO2N. dual approach further complemented discrimination mechanism evaluates unselected identify potential may exist. effectiveness proposed validated field experiment data from HFSWR Bohai Sea region, demonstrating capability accurately complex data.

Language: Английский

Citations

0
An efficient linear-extrapolation catch-fish algorithm for maximizing the harvested power from thermoelectric generators sources DOI

AL-Wesabi Ibrahim,

Jiazhu Xu, Hassan M. Hussein Farh

et al.

Applied Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 125916 - 125916

Published: Feb. 1, 2025

Language: Английский

Citations

0
A Labor Division Artificial Gorilla Troops Algorithm for Engineering Optimization DOI Creative Commons

C. L. Liu,

Bowen Wu, Liangkuan Zhu

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(3), P. 127 - 127

Published: Feb. 20, 2025

The Artificial Gorilla Troops Optimizer (GTO) has emerged as an efficient metaheuristic technique for solving complex optimization problems. However, the conventional GTO algorithm a critical limitation: all individuals, regardless of their roles, utilize identical search equations and perform exploration exploitation sequentially. This uniform approach neglects potential benefits labor division, consequently restricting algorithm’s performance. To address this limitation, we propose enhanced Labor Division (LDGTO), which incorporates natural mechanisms division outcome allocation. In phase, stimulus-response model is designed to differentiate tasks, enabling gorilla individuals adaptively adjust based on environmental changes. allocation three behavioral development modes—self-enhancement, competence maintenance, elimination—are implemented, corresponding developmental stages: elite, average, underperforming individuals. performance LDGTO rigorously evaluated through benchmark test suites, comprising 12 unimodal, 25 multimodal, 10 combinatorial functions, well two real-world engineering applications, including four-bar transplanter mechanism design color image segmentation. Experimental results demonstrate that consistently outperforms variants seven state-of-the-art algorithms in most cases.

Language: Английский

Citations

0
Optimal sizing of fuel cell hybrid electric Heavy-Duty tractor with minimum of unit mileage cost DOI
Xiaoyu Wang, Shouwen Yao, Pengyu Li

et al.

Energy Conversion and Management, Journal Year: 2025, Volume and Issue: 330, P. 119674 - 119674

Published: Feb. 26, 2025

Language: Английский

Citations

0
A Multi-Strategy Parrot Optimization Algorithm and Its Application DOI Creative Commons
Yang Yang,

Maosheng Fu,

Xiancun Zhou

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(3), P. 153 - 153

Published: March 2, 2025

Intelligent optimization algorithms are crucial for solving complex engineering problems. The Parrot Optimization (PO) algorithm shows potential but has issues like local-optimum trapping and slow convergence. This study presents the Chaotic–Gaussian–Barycenter (CGBPO), a modified PO algorithm. CGBPO addresses these problems in three ways: using chaotic logistic mapping random initialization to boost population diversity, applying Gaussian mutation updated individual positions avoid premature convergence, integrating barycenter opposition-based learning strategy during iterations expand search space. Evaluated on CEC2017 CEC2022 benchmark suites against seven other algorithms, outperforms them convergence speed, solution accuracy, stability. When applied two practical problems, demonstrates superior adaptability robustness. In an indoor visible light positioning simulation, CGBPO’s estimated closer actual ones compared PO, with best coverage smallest average error.

Language: Английский

Citations

0
Short-term power forecasting of photovoltaic generation based on CFOA-CNN-BiLSTM-Attention DOI
Bing Li,

Haizheng Wang,

Jinghua Zhang

et al.

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

Language: Английский

Citations

0
Efficiency Analysis of Binary Metaheuristic Optimization Algorithms for Uncapacitated Facility Location Problems DOI
Tahir Sağ, Aysegul IHSAN

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 112968 - 112968

Published: March 1, 2025

Language: Английский

Citations

0