Опубликована: Янв. 1, 2024
Язык: Английский
Опубликована: Янв. 1, 2024
Язык: Английский
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
12Artificial Intelligence Review, Год журнала: 2025, Номер 58(3)
Опубликована: Янв. 6, 2025
Abstract Numerical optimization and point cloud registration are critical research topics in the field of artificial intelligence. The differential evolution algorithm is an effective approach to address these problems, LSHADE-SPACMA, winning CEC2017, a competitive variant. However, LSHADE-SPACMA’s local exploitation capability can sometimes be insufficient when handling challenges. Therefore, this work, we propose modified version LSHADE-SPACMA (mLSHADE-SPACMA) for numerical registration. Compared original approach, work presents three main innovations. First, present precise elimination generation mechanism enhance algorithm’s ability. Second, introduce mutation strategy based on semi-parametric adaptive rank-based selective pressure, which improves evolutionary direction. Third, elite-based external archiving mechanism, ensures diversity population accelerate convergence progress. Additionally, utilize CEC2014 (Dim = 10, 30, 50, 100) CEC2017 test suites experiments, comparing our against: (1) 10 recent CEC winner algorithms, including LSHADE, EBOwithCMAR, jSO, LSHADE-cnEpSin, HSES, LSHADE-RSP, ELSHADE-SPACMA, EA4eig, L-SRTDE, LSHADE-SPACMA; (2) 4 advanced variants: APSM-jSO, LensOBLDE, ACD-DE, MIDE. results Wilcoxon signed-rank Friedman mean rank demonstrate that mLSHADE-SPACMA not only outperforms but also surpasses other high-performance optimizers, except it inferior L-SRTDE CEC2017. Finally, 25 cases from Fast Global Registration dataset applied simulation analysis potential developed technique solving practical problems. code available at https://github.com/ShengweiFu?tab=repositories https://ww2.mathworks.cn/matlabcentral/fileexchange/my-file-exchange
Язык: Английский
Процитировано
6Expert Systems with Applications, Год журнала: 2025, Номер 268, С. 126320 - 126320
Опубликована: Янв. 5, 2025
Язык: Английский
Процитировано
2Swarm and Evolutionary Computation, Год журнала: 2024, Номер 88, С. 101608 - 101608
Опубликована: Май 22, 2024
Язык: Английский
Процитировано
6Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125411 - 125411
Опубликована: Сен. 1, 2024
Язык: Английский
Процитировано
6Artificial Intelligence Review, Год журнала: 2024, Номер 57(10)
Опубликована: Сен. 5, 2024
Язык: Английский
Процитировано
5Computers in Biology and Medicine, Год журнала: 2025, Номер 186, С. 109587 - 109587
Опубликована: Янв. 2, 2025
Язык: Английский
Процитировано
0Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 111043 - 111043
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0Опубликована: Фев. 16, 2025
Язык: Английский
Процитировано
0International Journal of Data Science and Analytics, Год журнала: 2025, Номер unknown
Опубликована: Апрель 18, 2025
Язык: Английский
Процитировано
0