title: Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.
abstract: The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.
authors.affiliation: Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia.
authors.forename: Kian Sheng
authors.initials: KS
authors.lastname: Lim
authors.forename: Zuwairie
authors.initials: Z
authors.lastname: Ibrahim
authors.forename: Salinda
authors.initials: S
authors.lastname: Buyamin
authors.forename: Anita
authors.initials: A
authors.lastname: Ahmad
authors.forename: Faradila
authors.initials: F
authors.lastname: Naim
authors.forename: Kamarul Hawari
authors.initials: KH
authors.lastname: Ghazali
authors.forename: Norrima
authors.initials: N
authors.lastname: Mokhtar
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008962:Models, Theoretical; D009716:Numerical Analysis, Computer-Assisted