A Bi-Objective Field-Visit Planning Problem for Rapid Needs Assessment under Travel-Time Uncertainty

Mohammadmehdi Hakimifar, Vera C. Hemmelmayr and Fabien Tricoire
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Mohammadmehdi Hakimifar: Department of Global Business and Trade, Vienna University of Economics and Business, 1020 Vienna, Austria
Vera C. Hemmelmayr: Department of Global Business and Trade, Vienna University of Economics and Business, 1020 Vienna, Austria
Fabien Tricoire: Department of Global Business and Trade, Vienna University of Economics and Business, 1020 Vienna, Austria

Sustainability, 2022, vol. 14, issue 5, 1-16

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.

Keywords: humanitarian needs assessment; multi-objective; robust optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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