Abstract

After a sudden-onset disaster strikes, relief agencies usually dispatch assessment teams to the affected region to quickly investigate the impacts of the disaster on the affected communities. Within this process, assessment teams should compromise between the two conflicting objectives of a “faster” assessment, which covers the needs of fewer community groups, and a “better” assessment, i.e., covering more community groups over a longer time. Moreover, due to the possible effect of the disaster on the transportation network, assessment teams need to make their field-visit planning decisions under travel-time uncertainty. This study considers the two objectives of minimizing the total route duration and maximizing the coverage ratio of community groups, as well as the uncertainty of travel times, during the rapid needs assessment stage. In particular, within our bi-objective solution approach, we provide the set of non-dominated solutions that differ in terms of total route duration and the vector of community coverage ratio at different levels of travel-time uncertainty. Moreover, we provide an in-depth analysis of the amount of violation of maximum allowed time for decision makers to see the trade-offs between infeasibility and solution quality. We apply the robust optimization approach to tackle travel-time uncertainty due to its advantages in requiring fewer data for uncertain parameters and immunizing a feasible solution under all possible realizations.

Highlights

  • After a sudden-onset disaster, humanitarian organizations begin mobilizing healthcare facilities, equipment and relief items to assist the affected area

  • We extend the literature on humanitarian relief by considering both bi-objectives and uncertainty of travel times during the rapid needs assessment (RNA) stage, which addresses the two conflicting objectives of minimizing the total route duration and maximizing the vector of coverage ratio during the RNA stage

  • We focus on the bi-objective setting of the Selective Assessment Routing Problem” (SARP), which aims to find the best tradeoff between minimizing the total route duration and maximizing the vector of coverage ratio

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Summary

Introduction

After a sudden-onset disaster, humanitarian organizations begin mobilizing healthcare facilities, equipment and relief items to assist the affected area. Beforehand, it is of high importance to evaluate the local capacity on the field and the needs of the affected communities to guide the decisions needed to provide appropriate and effective assistance [1]. This quick evaluation of the impacted region is called rapid needs assessment (RNA) and usually starts as early as a few hours after the occurrence of a disaster, aiming to evaluate the disaster’s impact on various community groups. The information gathered by assessment teams helps humanitarian agencies to effectively satisfy the needs of affected communities in times of great need [4]

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