Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters: A case study of the 2015 Nepal earthquake

Hossein Baharmand,Tina Comes,Matthieu Lauras

doi:10.1016/j.ijdrr.2019.101455

Hossein Baharmand, Tina Comes + Show 1 more

Open Access

https://doi.org/10.1016/j.ijdrr.2019.101455

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Abstract

In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simulations. Our approach supports determining what trade-offs actually matter to facilitate discussions in the presence of multiple stakeholders. To validate our proposal, we extend a location-allocation model and apply our approach to an actual data-set from the 2015 Nepal earthquake response. Our analyses show that with the relative importance of covering demands ≤0.4, the trade-offs between logistics costs and response time affects the numbers and locations of RDCs considerably. We show through a small experiment that the outputs of our approach can effectively support group decision-making to develop relief plans in disasters response.

Highlights

The response to sudden-onset disasters is typically characterised by the influx of many organisations and individuals that rush to help the people in need
By extending the coverage values to higher than % 100, the divergence between the Pareto optimal solutions and values for United Nations (UN) WFP solution increased considerably
Missing criteria and/or constraints - The mathematical model that we adapted in our study aims at locating relief distribution centres (RDCs) based on logistics costs, response time, and demand coverage

Summary

Introduction

The response to sudden-onset disasters is typically characterised by the influx of many organisations and individuals that rush to help the people in need. According to Wu & Xu [5]; conflicting objectives can challenge and prolong the process of finding a consensus in group decisions This challenge is prominent in international disaster response, characterised by many actors working under pressure, and examples have been observed for instance in inter-organisational forums, such as inter-cluster or clusters [2,6]. Decision-making after sudden-onset disasters is a challenging task because of ‘ill-structured problems; uncertain dynamic environments; shifting, ill-defined, or competing goals; time stress; high stakes; [and] multiple players’ [22]. To cope with this complexity, humanitarian decision-making guidelines suggest that ‘decisions should be made by a group rather than by individuals’ [2,23,24,25]. Group decision-making, where it relies on consensus, can be slow and cumbersome [26,27,28]

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