A5061155326- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Icing and De-icing Technologies
- Smart Grid Security and Resilience
- Advanced Image and Video Retrieval Techniques
- Machine Learning and ELM
- Aerospace Engineering and Energy Systems
- Network Security and Intrusion Detection
Dalian University of Technology
2025
Northeast Forestry University
2022-2024
Nanchang University
2024
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...
<abstract><p>Aquila Optimizer (AO) and African Vultures Optimization Algorithm (AVOA) are two newly developed meta-heuristic algorithms that simulate several intelligent hunting behaviors of Aquila vulture in nature, respectively. AO has powerful global exploration capability, whereas its local exploitation phase is not stable enough. On the other hand, AVOA possesses promising capability but insufficient mechanisms. Based on characteristics both algorithms, this paper, we...
Honey badger algorithm (HBA) is a recently developed meta-heuristic algorithm, which mainly simulates the dynamic search behavior of honey in wild nature. Similar to other basic algorithms, HBA may suffer from weakness poor convergence accuracy, inadequate balance between exploration and exploitation, ease getting trapped into local optima. In order address these drawbacks, this paper proposes an enhanced (EHBA) improve quality method three aspects. First, we introduce highly disruptive...