The Robust Capacitated Vehicle Routing Problem Under Demand Uncertainty

Chrysanthos E. Gounaris (), Wolfram Wiesemann () and Christodoulos A. Floudas ()
Additional contact information
Chrysanthos E. Gounaris: Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544
Wolfram Wiesemann: Imperial College Business School, London SW7 2AZ, United Kingdom
Christodoulos A. Floudas: Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544

Operations Research, 2013, vol. 61, issue 3, 677-693

Abstract: The robust capacitated vehicle routing problem (CVRP) under demand uncertainty is studied to address the minimum cost delivery of a product to geographically dispersed customers using capacity-constrained vehicles. Contrary to the deterministic CVRP, which postulates that the customer demands for the product are deterministic and known, the robust CVRP models the customer demands as random variables, and it determines a minimum cost delivery plan that is feasible for all anticipated demand realizations. Robust optimization counterparts of several deterministic CVRP formulations are derived and compared numerically. Robust rounded capacity inequalities are developed, and it is shown how they can be separated efficiently for two broad classes of demand supports. Finally, it is analyzed how the robust CVRP relates to the chance-constrained CVRP, which allows a controlled degree of supply shortfall to decrease delivery costs.

Keywords: programming; robust optimization; transportation; vehicle routing; probability; chance constraints (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (45)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1120.1136 (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:oropre:v:61:y:2013:i:3:p:677-693

Access Statistics for this article

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