Grouped Grey Wolf Optimizer with differential evolution for global Optimizer and test scheduling for Support vector regression
- Resource Type
- Conference
- Authors
- Wang, Senlin; Fan, Renhao; Chen, Xiangye; Chen, Hao
- Source
- 2023 6th International Symposium on Autonomous Systems (ISAS) Autonomous Systems (ISAS), 2023 6th International Symposium on. :1-5 Jun, 2023
- Subject
- Aerospace
Robotics and Control Systems
Transportation
Support vector machines
Autonomous systems
Wind speed
Metaheuristics
Space exploration
Convergence
GWO
DE
Optimizer
Global search
- Language
This paper presents a new approach to optimization, called the grouped grey wolf optimizer (GWO) with differential evolution. The proposed structure divides the grey wolves into two groups: the cooperative hunting and the random scout group. The hunting group is responsible for exploring unfamiliar environments and exploiting deeper search spaces, while the scout group conducts a global search using the differential evolution algorithm to prevent the optimizer from getting stuck in local optima. This approach strikes a balance between exploration and exploitation, resulting in improved convergence. There are three case studies that demonstrate a better global convergence.