Author
Listed:
- Esra Koca
- Nilay Noyan
- Hande Yaman
Abstract
We introduce a new class of two-stage stochastic uncapacitated facility location problems under system nervousness considerations. The location and allocation decisions are made under uncertainty, while the allocation decisions may be altered in response to the realizations of the uncertain parameters. A practical concern is that the uncertainty-adaptive second-stage allocation decisions might substantially deviate from the corresponding pre-determined first-stage allocation decisions, resulting in a high level of nervousness in the system. To this end, we develop two-stage stochastic programming models with restricted recourse that hedge against undesirable values of a dispersion measure quantifying such deviations. In particular, we control the robustness between the corresponding first-stage and scenario-dependent recourse decisions by enforcing an upper bound on the Conditional Value-at-Risk (CVaR) measure of the random CVaR-norm associated with the scenario-dependent deviations of the recourse decisions. We devise exact Benders-type decomposition algorithms to solve the problems of interest. To enhance the computational performance, we also develop efficient combinatorial algorithms to construct optimal solutions of the Benders cut generation subproblems, as an alternative to using an off-the-shelf solver. The results of our computational study demonstrate the value of the proposed modeling approaches and the effectiveness of our solution methods.
Suggested Citation
Esra Koca & Nilay Noyan & Hande Yaman, 2021.
"Two-stage facility location problems with restricted recourse,"
IISE Transactions, Taylor & Francis Journals, vol. 53(12), pages 1369-1381, December.
Handle:
RePEc:taf:uiiexx:v:53:y:2021:i:12:p:1369-1381
DOI: 10.1080/24725854.2021.1910883
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:53:y:2021:i:12:p:1369-1381. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.