Stochastic Vehicle Routing with Recourse

  • Inge Li Gørtz
  • Viswanath Nagarajan
  • Rishi Saket
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7391)


We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed – but costs here become more expensive by a factor λ.

We present an O(log2 n ·log())-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based ω(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.


Approximation Algorithm Vertex Cover Vehicle Route Problem Submodular Function Minimum Vertex Cover 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Inge Li Gørtz
    • 1
  • Viswanath Nagarajan
    • 2
  • Rishi Saket
    • 2
  1. 1.DTU InformaticsTechnical University of DenmarkDenmark
  2. 2.IBM T.J. Watson Research CenterUSA

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