Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

Autor: Kian Sheng Lim, Zuwairie Ibrahim, Salinda Buyamin, Anita Ahmad, Faradila Naim, Kamarul Hawari Ghazali, Norrima Mokhtar
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: The Scientific World Journal, Vol 2013 (2013)
Druh dokumentu: article
ISSN: 1537-744X
DOI: 10.1155/2013/510763
Popis: 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.
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