Abstract
In this paper, we introduce, model, and solve a clustered resource allocation and routing problem for humanitarian aid distribution in the event of an earthquake and subsequent tsunami. First, for the preparedness stage, we build a set of clusters to identify, classify, sort, focus, and prioritize the aid distribution. The clusters are built with k-means method and a modified version of the capacitated p-median model. Each cluster has a set of beneficiaries and candidate delivery aid points. Second, vehicle routes are strategically determined to visit the clusters for the response stage. A mixed integer linear programming model is presented to determine efficient vehicle routes, minimizing the aid distribution times. A vulnerability index is added to our model to prioritize aid distribution. A case study is solved for the city of Iquique, Chile.
Highlights
The vehicle routing problems that consider the nodes are grouped into clusters are usually known as generalized or clustered vehicle routing problems
We propose an ad-hoc capacitated p-median mixed-integer linear programming (MILP) model [41] to build clusters containing Aid Delivery Point (ADP) and Beneficiary Point (BP).This clustering method builds exactly p clusters, minimizing the distances weighted by the demand of BPs plus the distances between ADPs
We chose the International Airport of Iquique Diego Aracena (IQQ), as the central distribution center where the most humanitarian aid would arrive in a disaster
Summary
Chile is exposed to several types of catastrophic events, such as earthquakes, tsunamis, volcanic eruptions, wildfires, and technological events [2,3] The uncertainty of these events has generated an important interest in humanitarian aid management research to better prepare and respond and, save lives and reduce the people suffering in case of those catastrophic events. This article studies a clustered resource allocation and routing problem in the humanitarian aid distribution to reduce the distribution times to the final beneficiaries in case of an earthquake and tsunami. The humanitarian aid could be distributed to more than one ADP within each cluster (e.g., in Figure 1, Cluster 2 is visited by more than one vehicle). Our main contribution is to propose a quantitative methodology for organizing and distributing humanitarian aid in case of an earthquake and subsequent tsunami.
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