Non-linear integer programming based on particle swarm optimisation combining diversification and intensification Online publication date: Fri, 08-Oct-2010
by Takeshi Matsui, Masatoshi Sakawa, Kosuke Kato, Koichi Matsumoto
International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP), Vol. 2, No. 3, 2010
Abstract: In this paper, focusing on non-linear integer programming problems, we propose an approximate solution method based on particle swarm optimisation (PSO) proposed by Kennedy et al. And we developed a new PSO method which is applicable to discrete optimisation problems by incorporating a new method for generating initial search points, the rounding of values obtained by the move scheme and the revision of move methods. Furthermore, we showed the efficiency of the proposed PSO method by comparing it with an existing method through the application of them into the numerical examples. Moreover we expanded revised PSO method for application to non-linear integer programming problems and showed more efficiency than genetic algorithm. However, variance of the solutions obtained by the PSO method is large and accuracy is not so high. Thus, we consider improvement of accuracy introducing diversification and intensification.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Knowledge Engineering and Soft Data Paradigms (IJKESDP):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook