Global Best Local Neighborhood in Particle Swarm Optimization in Dynamic Environment

• Main Authors: Zalili, Musa, Nurul Izzatie Husna, Fauzi, Mohd Hafiz, Mohd Hassin, M. N. M., Kahar, Watada, Junzo
• Format: Article
• Language: English
• Published: American Scientific Publisher 2018
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/22888/1/48.%20Global%20best%20Local%20Neighborhood%20in%20Particle%20Swarm%20Optimization%20in%20Dynamic%20Environment1.pdf; http://umpir.ump.edu.my/id/eprint/22888/; https://doi.org/10.1166/asl.2018.12984
• Institution: Universiti Malaysia Pahang Al-Sultan Abdullah

The conventional Particle Swarm Optimization (PSO) still has weaknesses in finding optimal solutions especially in a dynamic environment. Therefore, we proposed a Global best Local Neighborhood in particle swarm optimization in order to solve the optimum solution in a dynamic environment. Based on the experimental results of 50 datasets, show that GbLN-PSO has the ability to find the quality solution in a dynamic environment.