Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders

Faradila, Naim and Kian, Sheng Lim and Salinda, Buyamin and Anita, Ahmad and Mohd Ibrahim, Shapiai and Marizan, Mubin and Dong, Hwa Kim (2014) Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders. The Scientific World Journal, 2014. pp. 1-21. ISSN 2356-6140 (print); 1537-744X (online). (Published)

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The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept ofmultiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume.The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms.

Item Type: Article
Additional Information: Article ID: 364179
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 25 May 2015 08:41
Last Modified: 26 Apr 2018 01:47
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