Particle swarm optimiser with hybrid multi-parent crossover and discrete recombination
by Dazhi Jiang; Sanyou Zeng; Hui Wang; Zhijian Wu
International Journal of Intelligent Information and Database Systems (IJIIDS), Vol. 5, No. 6, 2011

Abstract: Particle swarm optimiser (PSO) has shown good performance in lots of optimisation problems. However, it easily suffers from premature convergence when solving complex optimisation problems. In order to improve the performance of PSO, this paper presents an enhanced evolutionary algorithm named as PSO with hybrid multi-parent crossover and discrete recombination (PSOHMCDR), which is based on the characteristics of PSO, multi-parent crossover algorithm and differential evolution (DE). Experimental results show that PSOHMCDR outperforms other nine algorithms, including six PSO variants and three typical and effective DE variants.

Online publication date: Mon, 17-Oct-2011

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Information and Database Systems (IJIIDS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com