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Bi‐objective stochastic programming models for determining depot locations in disaster relief operations

Bi-objective stochastic programming models for determining depot locations in disaster relief operations
Authors: Stefan Rath; Michel Gendreau; Walter J. Gutjahr;

Bi‐objective stochastic programming models for determining depot locations in disaster relief operations

Abstract

AbstractThis paper presents two‐stage bi‐objective stochastic programming models for disaster relief operations. We consider a problem that occurs in the aftermath of a natural disaster: a transportation system for supplying disaster victims with relief goods must be established. We propose bi‐objective optimization models with a monetary objective and humanitarian objective. Uncertainty in the accessibility of the road network is modeled by a discrete set of scenarios. The key features of our model are the determination of locations for intermediate depots and acquisition of vehicles. Several model variants are considered. First, the operating budget can be fixed at the first stage for all possible scenarios or determined for each scenario at the second stage. Second, the assignment of vehicles to a depot can be either fixed or free. Third, we compare a heterogeneous vehicle fleet to a homogeneous fleet. We study the impact of the variants on the solutions. The set of Pareto‐optimal solutions is computed by applying the adaptive Epsilon‐constraint method. We solve the deterministic equivalents of the two‐stage stochastic programs using the MIP‐solver CPLEX.

Countries
Canada, Austria
Keywords

Stochastic programming, LOGISTICS, 101015 Operations Research, stochastic programming, 101019 Stochastics, 101015 Operations research, humanitarian logistics, MANAGEMENT, disaster management, multiobjective optimization, EARTHQUAKE, HUMANITARIAN OPERATIONS, 101019 Stochastik, Multi-objective and goal programming, Continuous location

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
62
Top 10%
Top 10%
Top 10%
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