EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
2444. A hybrid Lagrangian relaxation and Benders decomposition algorithm to solve stochastic hub location problems with profit maximization
Invited abstract in session MC-61: Hub Location, stream Locational Analysis.
Monday, 12:30-14:00Room: S10 (building: 101)
Authors (first author is the speaker)
| 1. | Dung Tran
|
| University of Edinburgh | |
| 2. | Nader Azizi
|
| University of Edinburgh | |
| 3. | Thomas Archibald
|
| Business School, University of Edinburgh |
Abstract
This research addresses the profit maximization and pricing in a capacitated single assignment hub location problem. We assume that the demand between pairs of nodes in the network is price-sensitive and it is subject to uncertainty. The problem is formulated as a two-stage stochastic programming model, and a hybrid algorithm combining Lagrangian relaxation and Benders decomposition is developed to efficiently obtain optimal solutions. We also discuss some acceleration techniques to improve the performance of the proposed algorithm. Some numerical results and managerial insights are presented.
Keywords
- Location
- Stochastic Models
- Algorithms
Status: accepted
Back to the list of papers