Title: | Hybrid Swarming Algorithm With Van Der Waals Force |
Author(s): | Yi Z; Hongda Y; Mengdi S; Yong X; |
Address: | "College of Electrical and Computer Science, Jilin Jianzhu University, Changchun, China" |
DOI: | 10.3389/fbioe.2022.806177 |
ISSN/ISBN: | 2296-4185 (Print) 2296-4185 (Electronic) 2296-4185 (Linking) |
Abstract: | "This paper proposes a hybrid swarming algorithm based on Ant Colony Optimization and Physarum Polycephalum Algorithm. And the Van Der Waals force is first applied to the pheromone update mechanism of the hybrid algorithm. The improved method can prevent premature convergence into the local optimal solution. Simulation results show the proposed approach has excellent in solving accuracy and convergence time. We also compare the improved algorithm with other advanced algorithms and the results show that our algorithm is more accurate than the literature algorithms. In addition, we use the capitals of 35 Asian countries as an example to verify the robustness and versatility of the hybrid algorithm" |
Keywords: | ant colony optimization hybrid physarum polycephalum algorithm swarming algorithm van der waals forces; |
Notes: | "PubMed-not-MEDLINEYi, Zhang Hongda, Yu Mengdi, Sun Yong, Xu eng Switzerland 2022/03/15 Front Bioeng Biotechnol. 2022 Feb 23; 10:806177. doi: 10.3389/fbioe.2022.806177. eCollection 2022" |