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

Wuke Li,

Xiong Yang,

Yuchen Yin

и другие.

Biomimetics, Год журнала: 2024, Номер 10(1), С. 14 - 14

Опубликована: Дек. 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.

Язык: Английский

Artificial lemming algorithm: a novel bionic meta-heuristic technique for solving real-world engineering optimization problems DOI Creative Commons
Yaning Xiao, Hao Cui, Ruba Abu Khurma

и другие.

Artificial Intelligence Review, Год журнала: 2025, Номер 58(3)

Опубликована: Янв. 6, 2025

The advent of the intelligent information era has witnessed a proliferation complex optimization problems across various disciplines. Although existing meta-heuristic algorithms have demonstrated efficacy in many scenarios, they still struggle with certain challenges such as premature convergence, insufficient exploration, and lack robustness high-dimensional, nonconvex search spaces. These limitations underscore need for novel techniques that can better balance exploration exploitation while maintaining computational efficiency. In response to this need, we propose Artificial Lemming Algorithm (ALA), bio-inspired metaheuristic mathematically models four distinct behaviors lemmings nature: long-distance migration, digging holes, foraging, evading predators. Specifically, migration burrow are dedicated highly exploring domain, whereas foraging predators provide during process. addition, ALA incorporates an energy-decreasing mechanism enables dynamic adjustments between exploitation, thereby enhancing its ability evade local optima converge global solutions more robustly. To thoroughly verify effectiveness proposed method, is compared 17 other state-of-the-art on IEEE CEC2017 benchmark test suite CEC2022 suite. experimental results indicate reliable comprehensive performance achieve superior solution accuracy, convergence speed, stability most cases. For 29 10-, 30-, 50-, 100-dimensional functions, obtains lowest Friedman average ranking values among all competitor methods, which 1.7241, 2.1034, 2.7241, 2.9310, respectively, 12 again wins optimal 2.1667. Finally, further evaluate applicability, implemented address series cases, including constrained engineering design, photovoltaic (PV) model parameter identification, fractional-order proportional-differential-integral (FOPID) controller gain tuning. Our findings highlight competitive edge potential real-world applications. source code publicly available at https://github.com/StevenShaw98/Artificial-Lemming-Algorithm .

Язык: Английский

Процитировано

5
Zero-shot low-dose CT denoising across variable schemes via strip-scanning diffusion models DOI
Bo Su, Jiabo Xu, Xiangyun Hu

и другие.

Neurocomputing, Год журнала: 2025, Номер unknown, С. 129828 - 129828

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Enhanced algorithm for hybrid renewable energy systems, optimized with battery storage: A case study in Dakhla region, Morocco DOI

Ali EL Marzougui,

Saïda Bahsine,

Aziz Oukennou

и другие.

Journal of Energy Storage, Год журнала: 2025, Номер 120, С. 116386 - 116386

Опубликована: Апрель 9, 2025

Язык: Английский

Процитировано

0
Multiple elite strategy enhanced RIME algorithm for 3D UAV path planning DOI Creative Commons

Cankun Xie,

Shaobo Li,

Xinqi Qin

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Сен. 17, 2024

With the wave of artificial intelligence sweeping world in recent years, UAVs is widely used various fields. UAV path planning has attracted much attention from scientists as an essential part work. In order to design efficient and reasonable 3D program, researchers have invented improved many algorithms. This paper proposes elite RIME algorithm for planning. First, we propose reverse learning population selection strategy based on piecewise mapping enhance diversity better exploration. Second, this a stochastic factor-controlled pool exploration so that difficult enter local optimum can explore global optimum. Then, hard frost puncture exploitation sine-cosine function find faster during process. Meanwhile, test performance proposed paper, compare it with 13 other intelligent optimization algorithms are classical popular nowadays 52 functions three sets, CEC2017, CEC2020, CEC2022, obtain competitive results. Finally, applied problem different terrain scenarios, ELRIME achieved good results all them. Especially 7-peak model, improves by factor two. 9-peak average value aspect also reduce cost 91 compared algorithm, more importantly, smallest fluctuation 30 runs, which among most stable 12-peak its stability significantly enhanced, terms worst-case cost, 340 RIME.

Язык: Английский

Процитировано

3
A novel Histogram Image Clustering Approach using Enhanced Firefly Algorithm with K-means and expanded exploitation of Aquila Optimizer DOI Creative Commons
Krishna Gopal Dhal, Arunita Das, Jorge Gálvez

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Авг. 1, 2024

Abstract One of the most popular methods used in field image segmentation is K-means (KM). However, some limitations are presented, computational time and initialization process cluster centers. This study provides a Histogram-Based KM (HBKM) clustering approach that incorporates modified Firefly Algorithm (FA) to overcome drawbacks. In histogram-based method, it implemented considering grey-level histograms rather than pixels. As result, complexity significantly decreases due number grey levels employed. Moreover, original procedure prone be trapped local optima. Consequently, proposed can avoid this issue based on exploitation exploration mechanisms Aquila Optimizer (AO) method. A rigorous experimental analysis for comparing performance method against several state-of-art Nature-Inspired Optimization Algorithms (NIOAs) approaches conducted. According study, suggested presents competitive results terms precision, uniformity, robustness segmented outcomes contrasted NIOA-based approaches.

Язык: Английский

Процитировано

0
A Novel Hybrid Improved RIME Algorithm for Global Optimization Problems DOI Creative Commons

Wuke Li,

Xiong Yang,

Yuchen Yin

и другие.

Biomimetics, Год журнала: 2024, Номер 10(1), С. 14 - 14

Опубликована: Дек. 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.

Язык: Английский

Процитировано

0