A partitioning algorithm for the mixed integer nonlinear programming problem
by Biket Ergüneş; Linet Özdamar; Onur Demir; Nur Gülcan
International Journal of Operational Research (IJOR), Vol. 28, No. 2, 2017

Abstract: An interval partitioning method (IPM) is proposed to solve the (non-convex) mixed integer nonlinear programming problem (MINLP). The MINLP is encountered in many application areas and solving this problem bears practical importance. This paper proposes an IPM where two tree search strategies (breadth first and mixed breadth/depth first) and three variable subdivision methods are implemented. Two proposed variable subdivision methods are novel and they prioritise variables hierarchically according to several features. The IPM is implemented on a set of non-convex MINLP instances extracted from the MINLP benchmarks and numerical results show that its performance is quite promising.

Online publication date: Tue, 10-Jan-2017

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 Operational Research (IJOR):
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