The Value of Flexibility in Robust Location–Transportation Problems

Amir Ardestani-Jaafari () and Erick Delage ()
Additional contact information
Amir Ardestani-Jaafari: Department of Decision Sciences, HEC Montréal, Montréal, Quebec H3T 2A7, Canada; Groupe d’études et de recherche en analyse des décisions (GERAD), Montréal, Québec H3T 1J4, Canada
Erick Delage: Department of Decision Sciences, HEC Montréal, Montréal, Quebec H3T 2A7, Canada; Groupe d’études et de recherche en analyse des décisions (GERAD), Montréal, Québec H3T 1J4, Canada

Transportation Science, 2018, vol. 52, issue 1, 189-209

Abstract: This article studies a capacitated fixed-charge multiperiod location–transportation problem in which, while the location and capacity of each facility must be determined immediately, the determination of the final production and distribution of products can be delayed until actual orders are received in each period. In contexts where little is known about future demand, robust optimization, namely using a budgeted uncertainty set, becomes a natural method for identifying meaningful decisions. Unfortunately, it is well known that these types of multiperiod robust decision problems are computationally intractable. To overcome this difficulty, we propose a set of tractable conservative approximations for the problem that each exploit to a different extent the idea of reducing the flexibility of the delayed decisions. While all of these approximation models outperform previous approximation models that have been proposed for this problem, each also has the potential to reach a different level of compromise between efficiency of resolution and quality of the solution. A row generation algorithm is also presented to address problem instances of realistic size. We also demonstrate that full flexibility is often unnecessary to reach nearly, or even exact, optimal robust locations and capacities for the facilities. Finally, we illustrate our findings with an extensive numerical study where we evaluate the effect of the amount of uncertainty on the performance and structure of each approximate solution that can be obtained.

Keywords: transportation; facility location; robust optimization; flexibility; conservative approximation; demand uncertainty (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
https://doi.org/10.1287/trsc.2016.0728 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:52:y:2018:i:1:p:189-209

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().