A multi-criteria stochastic programming approach for pre-positioning disaster relief supplies in Brazil

Abstract

Paper aims: Considering that disaster preparedness is essential for a prompt and effective response, this paper presents a study to locate disaster relief supplies.Originality: This paper marks the first time a multi-criteria stochastic methodology addresses humanitarian location problems. Research method:We propose a multi methodology approach that employs an optimization model and a multi-criteria decision analysis. Based on logistics costs and penalties assigned for unmet demand, a stochastic model minimizes the total operational cost of opening distribution centers for pre-positioning disaster relief supplies. As decisions in humanitarian operations have multiple criteria and small differences in costs may not be significant by considering other criteria, we perform an analysis of the stochastic model solutions through Multi-criteria Decision Analysis. Main findings:The findings show that the stochastics model leads to good results in uncertainty accommodation and that the consideration of qualitative and quantitative criteria improves decisions in humanitarian operations, especially when the supplies available are not enough to meet all the demand requirements.

An entropy-based approach for disaster risk assessment and humanitarian logistics operations planning in Colombia

“…For example, in the case of landslides and collapses, the aftermath response must be fast using search, rescue and excavation equipment. In the case of floods, there are greater needs for shelters, food and health services to the population (de Brito Jr et al, 2020). More detailed evidence and routing problems are left for further investigation because there are few examples of routing in low densely populated rural areas (Huang et al, 2018).…”

Food aid supply and distribution in insecure regions: world food programme operation analysis in Ethiopia

“…Two-stage models have increasingly been applied to humanitarian operations contexts (Grass & Fischer, 2016), Hoyos et al (2015) -for example for emergency relief distribution (Barbarosoǧlu & Arda, 2004;Chakravarty, 2014;Alem et al, 2016;Rath et al, 2016), relief supplies prepositioning (Salmerón & Apte, 2010;Falasca & Zobel, 2011;Rawls & Turnquist, 2012;Noyan et al, 2015;Charles et al, 2016;Condeixa et al, 2017), facility location (Murali et al, 2012;Brito Junior et al, 2020), and facility location considering vehicle routing (Mete & Zabinsky, 2010;Li et al, 2012;Caunhye et al, 2015). However, the majority of the studies consider natural and sudden-onset disasters.…”

“…The scenarios (15) represent seasonality effects throughout the year (such as the rainy season or "hunger period") that affect hub accessibility and beneficiaries' demand . Both scenarios and associated probabilities were discussed and validated by WFP Ethiopia's logistics experts in an expert panel, as suggested by Salmerón &Apte (2010) andBrito Junior et al (2020). Table 2 presents the possible realizations and the associated probabilities of the stochastic parameters assuming that the random variables (demand and hub accessibility) are independent.…”

“…Lien et al (2014), for example, use an objective function that maximizes the expected minimum fill rate among customers to maintain a specified level of equity. Multi-criteria methods can also be used when considering qualitative criteria in the decision-making process (Brito Junior et al, 2020).…”