Details

Autor(en) / Beteiligte

• Li, Lixian
• Lee, Jaewan

Titel

Hybrid Fireworks Algorithm with Dynamic Coefficients and Improved Differential Evolution

Ist Teil von

• Inteonet jeongbo hakoe nonmunji = Journal of Korean Society for Internet Information, 2021-04, Vol.22 (2), p.19-27

Ort / Verlag

한국인터넷정보학회

Erscheinungsjahr

2021

Link zum Volltext

Quelle

EBSCOhost Business Source Ultimate

Beschreibungen/Notizen

• Fireworks Algorithm (FWA) is a new heuristic swarm intelligent algorithm inspired by the natural phenomenon of the fireworks explosion. Though it is an effective algorithm for solving optimization problems, FWA has a slow convergence rate and less information sharing between individuals. In this paper, we improve the FWA. Firstly, explosion operator and explosion amplitude are analyzed in detail. The coefficient of explosion amplitude and explosion operator change dynamically with iteration to balance the exploitation and exploration. The convergence performance of FWA is improved. Secondly, differential evolution and commensal learning (CDE) significantly increase the information sharing between individuals, and the diversity of fireworks is enhanced. Comprehensive experiment and comparison with CDE, FWA, and VACUFWA for the 13 benchmark functions show that the improved algorithm was highly competitive.