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Strategic Planning for Disaster Recovery with Stochastic Last Mile Distribution

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6140))

Abstract

This paper considers the single commodity allocation problem (SCAP) for disaster recovery, a fundamental problem faced by all populated areas. SCAPs are complex stochastic optimization problems that combine resource allocation, warehouse routing, and parallel fleet routing. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This paper formalizes the specification of SCAPs and introduces a novel multi-stage hybrid-optimization algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. The algorithm was validated on hurricane disaster scenarios generated by Los Alamos National Laboratory using state-of-the-art disaster simulation tools and is deployed to aid federal organizations in the US.

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Author information

Authors and Affiliations

  1. Brown University, Providence, RI, 02912, USA

    Pascal Van Hentenryck & Carleton Coffrin

  2. Los Alamos National Laboratory, Los Alamos, NM, 87545, USA

    Russell Bent

Authors
  1. Pascal Van Hentenryck
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  2. Russell Bent
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  3. Carleton Coffrin
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Editor information

Editors and Affiliations

  1. DEIS, University of Bologna, Viale Risorgimento 2, 40136, Bologna, Italy

    Andrea Lodi , Michela Milano  & Paolo Toth ,  & 

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Van Hentenryck, P., Bent, R., Coffrin, C. (2010). Strategic Planning for Disaster Recovery with Stochastic Last Mile Distribution. In: Lodi, A., Milano, M., Toth, P. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2010. Lecture Notes in Computer Science, vol 6140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13520-0_35

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  • DOI: https://doi.org/10.1007/978-3-642-13520-0_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13519-4

  • Online ISBN: 978-3-642-13520-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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