Alma Mater:National Chengchi University, Taiwan
Education Level:Postgraduate (Postdoctoral)
[MORE]1. Awardee of Excellent Young Role Models from Tainan County, Taiwan 2. Leading Scientists of the World 2009 3. Who's Who in the World 2013-2021 4. Who's Who in Science and Engineering 2016-2017 5. Who's Who in Asia 2017-2018 6. 福建省福州市台湾人才库成员 7. 中国海外杰青汇中华交流团(CSP)成员 8. 福建工程学院「本科优秀毕业设计(论文)指导教师奖」
Impact Factor:2.2
Journal:Mathematics, 2025, vol. 13, no. 13, 2158. https://doi.org/10.3390/math13132158
Abstract:In recent decades, the rapid development of metaheuristic algorithms has outpaced theoretical understanding, with experimental evaluations often overshadowing rigorous analysis. While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. This paper systematically examines the challenges in developing robust, generalizable optimization techniques, advocating for a paradigm shift toward modular, transparent frameworks. A comprehensive review of the existing limitations in metaheuristic algorithms is presented, along with actionable strategies to mitigate biases and enhance algorithmic performance. Through emphasis on theoretical rigor, reproducible experimental validation, and open methodological frameworks, this work bridges critical gaps in algorithm design. The findings support adopting scientifically grounded optimization approaches to advance operational applications.
Indexed by:Journal paper
Document Code:2158
Discipline:Natural Science
Document Type:J
Volume:13
Issue:13
ISSN No.:2227-7390
Translation or Not:no
Date of Publication:2025-07-01
Included Journals:SCI
First Author:Chia-Hung Wang
Co-author:Kun Hu,Xiaojing Wu,Yufeng Ou
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