Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems

Optimization problems are widespread across various fields, including industry, agriculture, and healthcare. Metaheuristic algorithms (MAs) are commonly employed to solve these problems due to their flexibility and robustness. However, despite their success, MAs inspired by plant evolutionary strate...

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Bibliographic Details
Published in:	International journal of computational intelligence systems Vol. 18; no. 1; pp. 117 - 22
Main Authors:	Cheng, Hongwei, Li, Jun, Zhang, Xiaoming, Li, Tingjuan, Zhang, Panpan
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 15.05.2025 Springer Nature B.V Springer
Subjects:	Adaptation Algorithms Artificial Intelligence Computational Intelligence Control Convergence Design Design engineering Design optimization Engineering Environmental conditions Evolution Exploitation Global optimization Heuristic methods Mathematical Logic and Foundations Mechatronics Metaheuristic algorithms Multi-population evolution Optimization algorithm framework Optimization algorithms Performance evaluation Plant population evolution Plant populations Research Article Robotics Robustness (mathematics) Seeds Strategy Task complexity Multi-population evolution Optimization algorithm framework Plant population evolution Metaheuristic algorithms
ISSN:	1875-6883, 1875-6891, 1875-6883
Online Access:	Get full text
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