ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
advertisementadvertisement
Discrete Applied Mathematics
Volume 82, Issues 1-3, 2 March 1998, Pages 15-25
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Purchase PDF (572 K)

 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/S0166-218X(97)00129-7    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1998 Published by Elsevier Science B.V.

Contribution

On the quality of local search for the quadratic assignment problem

Eric Angel and Vassilis ZissimopoulosCorresponding Author Contact Information, E-mail The Corresponding Author

Université de Paris Sud, LRI, CNRS-URA 410, Centre d'Orsay, 91405, Orsay, France

Available online 19 June 1998.

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Abstract

Local search is widely used to solve approximately NP-complete combinatorial optimization problems. But, little is known about quality of obtained local minima, for a given neighborhood. We concentrate on one of the most difficult optimization problems, the Quadratic Assignment Problem, and we give an upper bound for the quality of solutions obtained with deepest local search. Moreover, other recently established results on the traveling salesman problem, the graph bipartitioning problem and the maximum independent set problem can be deduced as particular cases.

Author Keywords: Local search; Quadratic assignment problem; Maximum independent set

Article Outline

• References

 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.