Humanitarian Relief Supply Chains Research Articles

Comparative study of robust optimization model of multimaterial emergency logistics in an uncertain environment

AbstractGiven the significance of objective functions in alleviating human suffering within the humanitarian relief supply chain, it is imperative to consider both logistics costs and the cost of deprivation as ideal targets. This study investigates a multimaterial single‐cycle stochastic mixed integer model, integrating uncertainties about post‐disaster demand, supply survival, and road networks. An innovative heuristic approach is used to solve the stochastic facility location problem, which minimizes unfulfilled requests and response times in lexicographic order. This research also compares the cost‐minimization model of the pre‐positioning problem to an alternative model that maximizes demand satisfaction under resource constraints. Empirical validation through numerous case studies and solutions confirms the effectiveness and feasibility of the alternative model. The results of our experiments consistently demonstrate that the best solution provided by the alternative model not only satisfies the minimum cost model but also surpasses the conventional problem, without compromising performance. Consequently, it is crucial to avoid the cost‐minimization approach at the expense of human suffering.

Integrating pre and post-disaster activities for designing an equitable humanitarian relief supply chain

The design of an efficient humanitarian relief supply chain (HRSC) for disaster management depends on the integration of pre- and post-disaster decisions, which reduces the suffering of the victims and saves lives. The use of strategies such as quantity flexibility contracts in the pre-disaster phase and evacuation management in the post-disaster phase significantly increase the efficiency of HRSCs for disaster management. Therefore, in this paper, for the first time, a comprehensive two-stage stochastic mixed-integer linear programming model is presented for integrating the pre- and post-disaster activities for possible disasters such as floods and earthquakes by considering quantity flexibility contract and equitable relief goods distribution. In addition, the proposed model determines the location of warehouses and inventory levels in these warehouses in the pre-disaster phase. It also deals with public donations and budget planning, planning vehicles and helicopters, locating hospitals and shelters, and optimizing the inventory flow between echelons in the post-disaster phase. In the proposed model, the quantity flexibility contract is applied to decrease the inventory level in the pre-disaster phase, and reduce the supply risk in the post-disaster phase. The efficiency and performance of the proposed model are evaluated using the data related to a possible earthquake in Karaj (one of the metropolises of Iran).

Supply chain resilience in mindful humanitarian aid organizations: the role of big data analytics

PurposeThe purpose of this paper is to understand the nomological network of associations between collective mindfulness and big data analytics in fostering resilient humanitarian relief supply chains.Design/methodology/approachThe authors conceptualize a research model grounded in literature and test the hypotheses using survey data collected from informants at humanitarian aid organizations in Africa and Europe.FindingsThe findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics.Originality/valueThis is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.

A disaster relief commodity supply chain network considering emergency relief volunteers: a case study

PurposeThe number of natural and man-made disasters is remarkable and threatened human lives at the time of occurrence and also after that. Therefore, an efficient response following a disaster can eliminate or mitigate the adverse effects. This paper aims to help address those challenges related to humanitarian logistics by considering disaster network design under uncertainty and the management of emergency relief volunteers simultaneously.Design/methodology/approachIn this paper, a robust fuzzy stochastic programming model is proposed for designing a relief commodity supply chain network in a disaster by considering emergency relief volunteers. To demonstrate the practicality of the proposed model, a case study is presented for the 22 districts of Tehran and solved by an exact method.FindingsThe results indicate that there are many parameters affecting the design of a relief commodity supply chain network in a disaster, and also many parameters should be controlled so that, the catastrophe is largely prevented and the lives of many people can be saved by sending the relief commodity on time.Practical implicationsThis model helps decision-makers and authorities to explore optimal location and allocation decisions without using complex optimization algorithms.Originality/valueTo the best of the authors’ knowledge, employee workforce management models have not received adequate attention despite their role in relief and recovery efforts. Hence, the proposed model focuses on the problem of managing employees and designing a disaster logistics network simultaneously. The robust fuzzy stochastic programming method is applied for the first time for controlling the uncertainties in the design of humanitarian relief supply chains.

HUMANITARIAN RELIEF SUPPLY CHAIN PERFORMANCE EVALUATION BY A SCOR BASED TRAPEZOIDAL TYPE-2 FUZZY MULTI CRITERIA DECISION MAKING METHODOLOGY: AN APPLICATION IN TURKEY

Determining the most important criteria to evaluate Humanitarian Relief Supply Chain (HRSC) performance is aimed in this study. For this purpose, Supply Chain Operations Reference (SCOR) model is adapted to HRSC. A trapezoidal type-2 fuzzy Analytic Hierarchy Process (T2F-AHP) methodology is proposed to evaluate the criteria influencing the performance of the HRSC, and also evaluate different Non-Governmental Organizations’ performances operating in Turkey as a real case study. Results of this methodology is aimed to be used by both governmental and non-governmental organizations to improve their HRSC strategies. Lastly, results are discussed with sensitivity analysis to demonstrate the feasibility and applicability of the proposed methodology.

Supply chain risks in humanitarian relief operations: a case of Cyclone Idai relief efforts in Zimbabwe

PurposeThe rising threat of tropical cyclones in Zimbabwe is of great importance in establishing the general sources of humanitarian supply chain risks and assessing their negative impact on relief operations. There is a scarcity of studies that collate such evidence toward enhanced humanitarian supply chains in Southern Africa. With this in mind, this study explored scattered evidence on supply chain risks in the delivery of humanitarian aid to victims of Cyclone Idai in Zimbabwe.Design/methodology/approachThis reflective study evaluates supply chain risks associated with Cyclone Idai humanitarian relief operations through qualitative in-depth interviews with relevant actors in the field. The data were triangulated with secondary information from associated publications, blogs and newspapers to reflect the truth about the phenomena under investigation.FindingsThe results show that Cyclone Idai disaster response operations were adversely affected by social, economic and political/governmental risk factors. In the same breath, poor or inadequate infrastructure and environmental factors were also contributing factors toward the futility of humanitarian relief operations.Practical implicationsThis study is significant as it endeavors to contribute toward humanitarian supply chain management, specifically in assisting humanitarian organizations with suggested strategies that would work toward making humanitarian relief supply chains more resilient. However, more research needs to be done toward optimized implementation strategies for the suggested framework.Originality/valueIt is to the best knowledge of these researchers that this is a unique study carried out to examine humanitarian supply chain risk factors in Cyclone Idai relief operations in Zimbabwe.

Designing a sustainable humanitarian relief logistics model in pre- and postdisaster management

In this study, a three-level relief chain problem is proposed in pre- and postdisaster phases in order to support sustainability in the context of humanitarian relief operations. We develop a comprehensive relief logistics network considering the strategic and tactical planning issues of facility location, procurement, and resource allocation, and including multi-objective mixed-integer stochastic programing model which minimizes total costs of the humanitarian relief supply chain (the costs of the preparedness and response phases), maximizes the social welfare (through maximizing the minimum satisfaction rates among the disaster areas), and minimizes the environmental impacts (ecological impacts of the packaging of relief goods, and CO2 emissions in transportation routes of the proposed network in pre- and postdisaster phases), simultaneously. The proposed multi-objective sustainable humanitarian relief logistics problem (SHRLP) is solved using the Compromise Programing (CP) technique and Lexicographic Optimization Method (LOM). Two numerical examples with different scales are provided based on surveying data of possible Tehran earthquakes. The results of solving numerical examples via CP and LOM methods are presented and compared. The efficient Pareto optimal solutions are also provided to examine different preferences of the objectives. LOM produces better solutions than the CP technique in terms of the satisfaction rates and fair distribution of relief items. Also, the results indicate that the novel model is able to survey and model both the sustainability approach and the uncertainty of a disaster relief condition in support of more efficient and effective plans for sustainable facility locations, and procurement and delivery of reliefs.

Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods

Disasters lead to breakdown of established Information and Communication Technology (ICT) infrastructure. ICT breakdown obstructs the channel to gather real-time last mile information directly from the disaster-stricken communities and thereby hampers the agility of humanitarian supply chains. This creates a complex, chaotic, uncertain, and restrictive environment for humanitarian relief operations, which struggles for credible information to prioritize and deliver effective relief services. In this paper, we discuss how satellite big data analytics built over real-time weather information, geospatial data and deployed over a cloud-computing platform aided in achieving improved coordination and collaboration between rescue teams for humanitarian relief efforts in the case of 2018 Kerala floods. The analytics platform made available to the stakeholders involved in the rescue operations led to timely logistical planning and execution of rescue missions. The developed platform improved the accuracy of information between the distressed community and the stakeholders involved and thereby increased the agility of humanitarian logistics and relief supply chains. This research proves the utility of fusing data sources that are normally sitting as islands of information using big data analytics to prioritize humanitarian relief operations.

A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains

This paper proposes a novel two-period option contract integrated with supplier selection and inventory prepositioning. A two-stage scenario-based mixed possibilistic-stochastic programming model is developed to cope with various uncertainties. The first stage's decisions include supplier selection and capacity reservation level at each supplier/period and the level of inventory prepositioning. Furthermore, decisions regarding the time and exercised amount are made in the second stage. Applicability of the model is validated through a real case study. Finally, several sensitivity analyses are conducted to examine the effect of important parameters on the solutions to gain useful managerial insights.

Microgrids for Disaster Management: An Ethical Risk Perspective

Microgrids are interconnected distributed energy generation and storage systems that can act as either an extension of the existing grid or operate independently of the grid, in so-called island mode [1]. As a power supply technology, microgrids are attractive as they can be more reliable than existing infrastructure and reduce societies? reliance on nonrenewable energy sources [1]. As a valid alternative to reliance on centralized electricity generation and grid distribution, microgrids have value that materializes when disasters render grids inoperable and microgrids remain as islands of service. It is these specific disaster conditions that reveal the latent value of microgrids as disaster management tools, whereas under nondisaster conditions, their value remains hidden. Microgrids can thus be leveraged to manage disaster relief efforts while remaining connected to donor sources and the broader humanitarian relief supply chain.

Humanitarian Organizations in International Disaster Relief: Understanding the Linkage Between Donors and Recipient Countries

This study explores how humanitarian organizations (HOs) link donors and recipients in a disaster relief coordination mechanism. Based on an analysis of real data collected from the financial tracking service, our results show that disaster assistance through the HO channel greatly exceeds the funding delivered by the non-HO channel. The severity of the disaster is positively correlated with the involvement of HOs. Disaster-stricken countries that belong to the Non-Aligned Movement receive more assistance through the HO channel. The recipients with less international trade may attract more HO-channel funding, but higher international tourism expenditures also may result in more HO-channel funding. We also found that the determinants of the disaster relief coordination path vary greatly in terms of trade openness, political regime, and geographic factors. Based on the analysis of the primary humanitarian relief supply chain, the results show that some countries prefer to donate through large international HOs (e.g., Japan and Canada), and other countries favor national level organizations (e.g., the UK and the USA). Finally, to improve the efficiency of international disaster relief, the paper suggests a coordination platform that involves the main donors, frequent recipients, HOs, and a Global Information Network that can assist in coordinating disaster relief activities.

A disaster typology towards informing humanitarian relief supply chain design

PurposeThe purpose of this paper is to construct a typology of a disaster that informs humanitarian-relief supply chain (HRSC) design across the stages of disaster relief.Design/methodology/approachIn addition to an interdisciplinary review of pertinent literature, this paper utilises a typology construction method to propose theoretically and methodologically sound dimensions of disasters.FindingsWhilst semantic arguments surrounding the concept of a “disaster” are ongoing, the authors propose three typologies based upon six dimensions that serve as interdependent variables informing resultant HRSC design considerations. These are speed of onset, time horizon, spatial considerations, affected population needs, perceived probability of occurrence and perceived magnitude of consequence. These combinational and independent relationships of the variables offer insight into key HRSC design-making considerations.Research limitations/implicationsThe study improves conceptual knowledge of disasters, distilling the concept to only the dimensions applicable to HRSC design, omitting other applications. The typologies provide empirical cell types based on extant literature, but do not apply the models towards new or future phenomena.Practical implicationsThis paper provides HRSC practitioners with normative guidance through a more targeted approach to disaster relief, with a focus on the impacted system and resulting interactions’ correspondence to HRSC design.Originality/valueThis paper provides three typological models of disasters uniquely constructed for HRSC design across the various stages of disaster relief.

Agent-based evaluation of humanitarian relief goods supply capability

Natural disasters cause great damage to lives, assets, and the economy. In disaster areas, relief goods are essential sources of life supplies, particularly in the post-disaster context. This study develops a prototype of a spatially explicit agent-based model and uses it to evaluate the deviation of end products between supply and demand for humanitarian relief goods in the areas affected by disaster within a specified time frame. The case modeled here is the supply of refined oil to areas affected by the 2008 Wenchuan earthquake in China. The approach focuses on supply and uses socio-spatial datasets, as well as transport and refined oil supply data. Based on the supply of refined oil to the disaster areas after the disaster, this study conducted a quantitative analysis using agent-based simulation of the humanitarian relief supply chain. The study finds that the approach is viable, despite the limitations of publicly available datasets on relief goods in China. The study asserts that this approach has potential in assisting policymakers seeking to identify system vulnerabilities and increase resilience in disaster-prone and disaster areas.

Optimization of humanitarian relief supply chain reliability: a case study of the Ya’an earthquake

This article seeks to propose a mathematical method to optimize the reliability of the humanitarian relief supply chain. Reliability and cost are both important in response to the disasters. To optimize the reliability of humanitarian relief supply chain and to find a trade-off between the reliability and cost, this article establishes a reliability integrated optimization model for the humanitarian relief supply chain and investigates the methods for optimizing the coordination between flow quantity and unit reliability, optimizes the allocation of reliability for each unit, to optimize the total reliability and cost of the humanitarian relief supply chain. To make the results of this article more applicable, this article applies a case study of the Ya’an earthquake to the built model and subsequently proves the related conclusions subsequently. These theoretical results can be used to improve the disaster operations efficiency of the humanitarian relief supply in the crisis state, achieve a win–win situation between the total reliability and cost.

A robust model for a humanitarian relief network with backup covering under disruptions: A real world application

In this paper a reliable and robust model for the humanitarian relief supply chain has been presented to deal with the risk of facility disruptions after an earthquake. Assignment of backup suppliers for affected population centers is considered in order to improve the reliability of the model. Employment of public local centers and defining a two-level structure for rescue centers was considered to raise the accessibility to population centers. A four-step methodology was suggested to define the input parameters of the model which were affected by the uncertainty associated with the magnitude of an earthquake. To investigate this uncertainty, the potential epicenters of probable earthquakes and their magnitudes were assumed as uncertain parameters and estimated with a set of scenarios. A scenario-based robust optimization approach was used to sweep over the uncertain parameters. In the proposed methodology, a practical three-factor function was described to determine the impact of an earthquake on rescue centers and demand points. A solution method was proposed based on Lagrangian relaxation method, whose computational efficiency was also examined. A case study in Tehran was used to show the performance of the model in addition to determine whether the proposed methodology was efficient and practical. The computational results revealed the efficiency of the proposed model and sensitivity analyses indicated that the proposed model could be useful in conditions where budget constraints exist.

Swift trust and commitment: The missing links for humanitarian supply chain coordination?

Coordination among actors in a humanitarian relief supply chain decides whether a relief operation can be or successful or not. In humanitarian supply chains, due to the urgency and importance of the situation combined with scarce resources, actors have to coordinate and trust each other in order to achieve joint goals. This paper investigated empirically the role of swift trust as mediating variable for achieving supply chain coordination. Based on commitment-trust theory we explore enablers of swift-trust and how swift trust translates into coordination through commitment. Based on a path analytic model we test data from the National Disaster Management Authority of India. Our study is the first testing commitment-trust theory in the humanitarian context, highlighting the importance of swift trust and commitment for much thought after coordination. Furthermore, the study shows that information sharing and behavioral uncertainty reduction act as enablers for swift trust. The study findings offer practical guidance and suggest that swift trust is a missing link for the success of humanitarian supply chains.

Humanitarian relief supply chain: a multi-objective model and solution

This paper models a humanitarian relief chain that includes a relief goods supply chain and an evacuation chain in case of a natural disaster. Optimum network flow is studied for both the chains by considering three conflicting objectives, namely demand satisfaction in relief chain, demand satisfaction in evacuation chain and overall logistics cost. The relief goods supply chain consists of three echelons: suppliers, relief camps and affected areas. The evacuation chain consists of two echelons: evacuation camps and affected areas. The model has been made more resilient by considering multiple paths between any two locations and disruption of camps and paths due to natural factors. The Mixed Integer Programming problem has been solved using NSGA-III and results have been compared to those from benchmark algorithms. The model has been successfully tested on generated real-life-like data.

Humanitarian Relief Supply Chain Performance Evaluation: A Literature Review

<p>Nowadays small, medium and severe disasters are threatening our world. One of the important role players in alleviating these traits are humanitarian relief supply chains. The increasing number of disasters in our planet earth urges the humanitarian relief supply chains to focus on the assurance of safety of the victims. In order for this to occur, these supply chains should work effectively and efficiently. This can be possible through considerable evaluation of their supply chain performance. In this paper a literature review on supply chain performance evaluation in general and humanitarian relief supply chain performance in particular is presented. Previously conducted researches from the year 2000 until the present time have been reviewed. The works were categorized according to writers, publication year, publishing journal, technique utilized and objective intended. Then an analysis was made on humanitarian relief supply chain literature with respect to the publishing journals and the research technique applied. The result shows that humanitarian relief supply chain evaluation is almost an untouched area which needs further study. Recent supply chain management techniques can be applied for the improved performance of these supply chains. Based on this result, Supply Chain Operations Reference (SCOR), Fuzzy Logic System, and Artificial Neural Networks are found to be the areas which need further study.</p>

Proactive and reactive inventory policies in humanitarian operations

Inventory planning for the pre- and post-disaster phases of disaster relief lifecycle is a challenging problem associated with the humanitarian relief supply chains. In this work, two mathematical models are presented encompassing the whole disaster relief lifecycle. By accounting for holding costs of perishable supplies, a two-stage stochastic programming model is first developed by which the inventory prepositioning locations, inventory levels, and shortterm distribution quantities are determined. For the recovery phase, this research adapts the well-known continuous review (Q, r) inventory model for relief warehouses while accounting for the inherent epistemic uncertainty in the required data by using the fuzzy programming. A case study of Iranian Red Cross is also provided to illustrate the applicability of the first model and to demonstrate how it supports the two first phases of disaster lifecycle. Additionally, a numerical example is presented to demonstrate the applicability of the (Q, r) model for the recovery phase. Lastly, the impact of penalty costs on the solutions is discussed.

An overview of humanitarian relief supply chains for victims of perennial flood disasters in Lagos, Nigeria (2010-2012)

Purpose – Lagos is flooded perennially due to its low-lying coastal location. Empirical studies on the impacts of the disaster and humanitarian relief for the victims are scanty. The purpose of this paper is to assess the causes and severity of the floods, the aids to victims and the supply chains in six flood-prone local government areas (LGAs) of the metropolis comparatively. Design/methodology/approach – Data were collected using a questionnaire instrument that was administered to 292 victims and/or residents of 42 flooded neighborhoods in six LGAs of Lagos in the years 2010-2012. The administration was some few weeks after major incidences were reported for the respective years. Findings – The results show that floods are recurrent in the areas during every wet season (between May and October), emanate from both natural and human-induced causes and lead to large-scale human displacement and loss of assets. Humanitarian reliefs are from neighbors, spiritual homes and relatives mostly and are supplied directly to victims. These suggest gloomy implications for sustainable disaster management, humanitarian services and supply chains. Areas for further studies are highlighted. Originality/value – Studies in humanitarian relief and supply chains are scanty in the part of the world. The paper is original and not been considered for publication elsewhere.