Year: 2022
Type: conference-paper
Abstract: In dealing with optimization problems, metaheuristic algorithms have attracted much attention due to their simple structure and flexible characteristics. Inspired by the principle of teaching students in accordance with their aptitude, this paper proposed a novel metaheuristic algorithm——Group Learning based Optimization (GLBO) Algorithm, this algorithm is suitable for continuous optimization problems. The main idea of this method is to divide a class into three study groups according to their scores, and formulate different study strategies for them according to the characteristics of each group, so as to improve the scores of the whole class. To verify the performance of the algorithm, it is tested on the CEC21 Benchmark suit and applied to UWB positioning. The results show that the proposed method has excellent performance when dealing with continuous optimization problems.
Authors: XiuWei Zhang, WenYi Zheng, Yong chen
Institution: Chongqing Normal University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4283258686