Equity and deprivation costs in humanitarian logistics

Gutjahr, Walter J.; Fischer, Sophie

doi:10.1016/j.ejor.2018.03.019

Cited by 92 publications

(42 citation statements)

References 26 publications

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“…Furthermore, Gutjahr and Fischer (2018) were able to show that the minimization of deprivation costs leads to unfair solutions in case of budget limitations. They therefore developed an approach that includes measures similar to the Gini-coefficient to increase the fairness of the resulting allocations.…”

Section: Multi-objective Nature Of Logistic Modelsmentioning

confidence: 99%

Public-private collaborations in emergency logistics: A framework based on logistical and game-theoretical concepts

et al. 2021

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Collaboration in emergency logistics can be beneficial for governmental actors when supply chains need to be set up immediately. In comparison to research on humanitarian-business partnerships, the body of literature on so-called Public-Private Emergency Collaborations (PPEC) remains scarce. Private companies are only rarely considered within research on emergency collaborations, although they could contribute to a more efficient supply of goods given their resources and existing communication networks. Based on this research gap, this paper develops a logistical and game-theoretical modeling framework for public-private emergency collaborations. We characterize both public and private actors' possible roles in emergency logistics based on literature research and real cases. Furthermore, we provide an overview on existing PPECs and the challenges they are confronted with. The concluding framework contains aspects from humanitarian logistics on the governmental side and from business continuity management (BCM) or corporate social responsibility (CSR) on the commercial side. To address the challenge of evaluating different objectives in a collaboration, we add a game-theoretical approach to highlight the incentive structure of both parties in such a collaboration. In this way, we contribute to the research field by quantitatively evaluating public-private collaboration in emergency logistics while considering the problem-specific challenge of the parties' different objectives.

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Section: Multi-objective Nature Of Logistic Modelsmentioning

confidence: 99%

Public-private collaborations in emergency logistics: A framework based on logistical and game-theoretical concepts

et al. 2021

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“…Many recent studies on facility location, in terms of penalties, address deprivation costs in the objective function as a way of assuming the penalty of shortages over time (Balcik et al, 2016;Boonmee et al, 2017;Cotes & Cantillo, 2019;Gutjahr & Fischer, 2018;Wang et al, 2017). However, the results obtained from the functions defined in Holguín-Veras et al (2016) and Pérez-Rodríguez & Holguín-Veras (2016), considering 72 hours for supply show very different values reaching 3,528%, when comparing these functions.…”

Section: Two-stage Stochastic Optimization Models In Humanitarian Operationsmentioning

confidence: 99%

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

Brito

Leiras

Yoshizaki

2020

Prod.

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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.

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“…Eisenhandler and Tzur (2016) address the problem of an efficient and fair distribution of perishable goods from food suppliers to welfare agencies serving people in need of food. Gutjahr and Fischer (2018) show that the deprivation cost concept, which has recently been proposed to derive suitable objective functions for humanitarian logistics models, can (and should) be extended to take the equity issue into account. The two lastmentioned works come close to our present article insofar as they also use the Gini index to quantify inequity, but both approaches are restricted to a deterministic situation.…”

Section: Inequality-averse Optimization In Humanitarian Operationsmentioning

confidence: 99%

Inequity-averse shelter location for disaster preparedness

2019

Self Cite

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We study the problem of selecting a set of shelter locations in preparation for natural disasters. Shelters provide victims of a disaster both a safe place to stay and relief necessities such as food, water and medical support. Individuals from the affected population living in a set of population points go to, or are transported to the assigned open shelters. We aim to take both efficiency and inequity into account, thus we minimize a linear combination of: (i) the mean distance between opened shelter locations and the locations of the individuals assigned to them; and (ii) Gini's Mean Absolute Difference of these distances. We develop a stochastic programming model with a set of scenarios that consider uncertain demand and disruptions in the transportation network. A chance constraint is defined on the total cost of opening the shelters and their capacity expansion. In this stochastic context, a weighted mean of the so-called ex ante and ex post versions of the inequity-averse objective function under uncertainty is optimized. Since the model can be solved to optimality only for small instances, we develop a tailored Genetic Algorithm (GA) that utilizes a mixed-integer programming subproblem to solve this problem heuristically for larger instances. We compare the performance of the mathematical program and the GA via benchmark instances where the model can be solved to optimality or near optimality. It turns out that the GA yields small optimality gaps in much shorter time for these instances. We run the GA also on Istanbul data to drive insights to guide decision-makers for preparation.

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Equity and deprivation costs in humanitarian logistics

Cited by 92 publications

References 26 publications

Public-private collaborations in emergency logistics: A framework based on logistical and game-theoretical concepts

Public-private collaborations in emergency logistics: A framework based on logistical and game-theoretical concepts

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

Inequity-averse shelter location for disaster preparedness

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