Relief Items Research Articles

Using containers as storage facilities in humanitarian logistics

Purpose – The purpose of this paper is to investigate the use of freight containers to store relief items instead of operating a permanent warehouse building. Design/methodology/approach – A mathematical model is developed to determine the location and quantity of containers as well as the type and amount of relief supplies to store in order to investigate the practicality of using freight containers for storage. The model is tested using earthquake risk data, estimates of population under risk, and the distances between cities. An experimental study is performed using Turkish Prime Ministry Disaster and Emergency Management Presidency (abbreviated as AFAD in Turkish) data for total number of relief supplies. Findings – Considering the earthquake risk of possible locations, the results of the study indicate the target locations for containers. The idea of using containers as storage facilities helped beneficiaries to be reached within a short distance and in an efficient way. Research limitations/implications – The presented model is not implemented in real life disaster relief operations even if it is tested with real earthquake risk, demand and distance data. Practical implications – To apply this model in practice, the container locations within cities should be determined and managerial operations such as maintenance, environmental, and security planning have to be considered. Originality/value – This study presents the first analysis of three sub-topics’ intersection: warehousing, pre-positioning in disaster relief, and containerization. To the best of authors’ knowledge, containers have not been considered for storage of relief items in humanitarian logistics before.

Humanitarian Logistics: A Clustering Methodology for Assisting Humanitarian Operations

In this paper, we propose a methodology to identify and classify regions by the type and frequency of disasters. The data on the clusters allow you to extract information that can be used in the preparedness phase as well as to identify the relief items needed to meet each cluster. Using this approach, the clusters are formed by using a computing tool that uses as the input the history data of the disasters in the Brazilian state of Santa Catarina, with a specific focus on: windstorms, hail, floods, droughts, landslides, and flash floods. The results show that the knowledge provided by the clustering analysis contributes to the decision making process in the response phase of Humanitarian Logistics (HL).

Robust humanitarian relief logistics network planning

Article history: Received September 10, 2013 Received in revised format 10 December 2013 Accepted January 12 2014 Available online January 24 2014 In recent years, death toll of natural and man-made disasters has increased at an appalling rate. Thus, disaster management and especially efficient management of humanitarian relief efforts seem to be essential. This paper presents a bi-objective mixed-integer mathematical model for Humanitarian Relief Logistics (HRL) operations planning, as an important part of the humanitarian relief efforts. This model determines optimal policies including location of warehouses, quantity of emergency relief items that should be held at each warehouse, and distribution plan to provide an emergency response pre-positioning strategy for disasters by considering two objectives. The first one minimizes the average response time and the second one minimizes the total operational cost including the fixed cost of establishing warehouses, the holding cost of unused supplies and the penalty cost of unsatisfied demand. The survival of prepositioned supplies, demand amount and routes condition following an event are considered under uncertainty in the model solved by a robust scenario-based approach. The robust approach is applied to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. The research demonstrates the applicability and usefulness of the proposed model on a case study on earthquake preparation in the Seattle area in USA. In addition, the work applies the Reservation Level Tchebycheff Procedure (RLTP) method to solve the bi-objective model in an interactive way with decision maker. This work provides practitioners, specifically planning teams, with a new approach to assist with disaster preparedness and to improve their logistics decisions. © 2014 Growing Science Ltd. All rights reserved.

A Framework to Compare OR Models for Humanitarian Logistics

A multitude of OR models – mainly mathematical programs – has been published in relevant journals to support decision-making in the field of humanitarian logistics. Due to the effort that comes with their application, these models are often not adapted by practitioners in humanitarian organizations. Clearly, one part of the effort relates to the comparison process in which the decision-maker has to choose the most appropriate model out of the available OR models. In this contribution, a framework is presented that should help decision-makers in the field of humanitarian logistics to compare available OR models. Three different ways how to compare OR models are introduced: based on the decision they support, based on the decision criteria and metrics they use, and based on their underlying methodology and assumptions. To serve as an illustration, two mathematical programs for the specification of stationary warehouses for relief items are compared with the help of this framework. In the long run, this framework will guide users of a methodological toolkit for humanitarian logistics to the most appropriate OR model for their decision problem. The development of such a methodological toolkit is the overarching goal of this work-in-progress.

Design of emergency logistics networks, taking efficiency, risk and robustness into consideration

This paper provides an integrated framework to design emergency logistics networks (ELNs) based upon efficiency, risk and robustness metrics. The mixed integer linear programming-based framework consists of strategic level design (SLD) and operational level plan (OLP) phases. The efficiency and risk are determined using transportation cost (TC) and relief item loss cost, respectively, in SLD phase while the robustness is analysed in terms of perturbed TC through diverse damage scenarios to major facilities in OLP phase. The applicability of the framework is demonstrated with two case studies using historical disaster records. The results show that this framework provides two options to decision-makers. One option is to design the optimal ELN based upon three integrated costs, while the other is to select ELNs based upon risk tolerance. We claim that the framework would provide significant insights to practitioners and researchers for design and implementation of ELN models.

The decision-making models for relief asset management and interaction with disaster mitigation

The World Health Organization defines a disaster as any occurrence that causes damage, destruction, ecological disruption, loss of human life, human suffering, deterioration of health and health services on a scale sufficient to warrant an extraordinary response from outside the affected community or area (Haghani and Oh, 1996 [1]). Natural disasters can be devastating in terms of human injuries and economic damages. For example, the two earthquakes that occurred in the Marmara region of Turkey in 1999 caused over 20,000 casualties and resulted in the collapse of more than 110,000 buildings (Karaman et al., 2008 [2]). The total cost of damage from these two earthquakes is estimated to range between 9 and 13 billion dollars (Bibbee et al., 2000 [3]). And in the recent Van, Erciş earthquakes, 644 people died and 35,000 houses collapsed (Van, Turkey Earthquake, 2011 [4]).It is obvious that earthquake disaster is a serious and intractable problem that threatens the ability of a nation to protect human lives and property losses. The extent of the casualties and economic damage calls for finding efficient solutions to important problems with the aim of enhancing the capability of reducing the impacts of such events and providing a quick and efficient response by rapidly supplying relief items such as emergency food, water, and medicine to those areas that are severely affected (Beamon and Balcik, 2008 [5]). The main motivation for this study is to reduce the number of casualties and to protect national properties (e.g. national infrastructure etc.) by showing disaster related problems' studies. Developing mathematical models for disaster-related problems and solving them by using operations research techniques have received increasing interest due to their efficiency in tackling these problems.

Fatigue self‐management: a survey of Chinese cancer patients undergoing chemotherapy

To examine Chinese cancer patients' fatigue self-management, including the types of self-management behaviours used, their confidence in using these behaviours, the degree of relief obtained and the factors associated with patients' use of fatigue self-management behaviours. Fatigue places significant burden on patients with cancer undergoing chemotherapy. While some studies have explored fatigue self-management in Western settings, very few studies have explored self-management behaviours in China. Cross-sectional self- and/or interviewer-administered survey. A total of 271 participants with self-reported fatigue in the past week were recruited from a specialist cancer hospital in south-east China. Participants completed measures assessing the use of fatigue self-management behaviours, corresponding self-efficacy, perceived relief levels plus items assessing demographic characteristics, fatigue experiences, distress and social support. A mean of 4.94 (± 2.07; range 1-10) fatigue self-management behaviours was reported. Most behaviours were rated as providing moderate relief and were implemented with moderate self-efficacy. Regression analyses identified that having more support from one's neighbourhood and better functional status predicted the use of a greater number of self-management behaviours. Separate regression analyses identified that greater neighbourhood support predicted greater relief from 'activity enhancement behaviours' and that better functional status predicted greater relief from 'rest and sleep behaviours'. Higher self-efficacy scores predicted greater relief from corresponding behaviours. A range of fatigue self-management behaviours were initiated by Chinese patients with cancer. Individual, condition and environmental factors were found to influence engagement in and relief from fatigue self-management behaviours. Findings highlight the need for nurses to explore patients' use of fatigue self-management behaviours and the effectiveness of these behaviours in reducing fatigue. Interventions that improve patients' self-efficacy and neighbourhood supports have the potential to improve outcomes from fatigue self-management behaviours.

Evaluation of the Irritable Bowel Syndrome Quality of Life (IBS-QOL) questionnaire in diarrheal-predominant irritable bowel syndrome patients

BackgroundDiarrhea-predominant irritable bowel syndrome (IBS-d) significantly diminishes the health-related quality of life (HRQOL) of patients. Psychological and social impacts are common with many IBS-d patients reporting comorbid depression, anxiety, decreased intimacy, and lost working days. The Irritable Bowel Syndrome Quality of Life (IBS-QOL) questionnaire is a 34-item instrument developed and validated for measurement of HRQOL in non-subtyped IBS patients. The current paper assesses this previously-validated instrument employing data collected from 754 patients who participated in a randomized clinical trial of a novel treatment, eluxadoline, for IBS-d.MethodsPsychometric methods common to HRQOL research were employed to evaluate the IBS-QOL. Many of the historical analyses of the IBS-QOL validations were used. Other techniques that extended the original methods were applied where more appropriate for the current dataset. In IBS-d patients, we analyzed the items and substructure of the IBS-QOL via item reduction, factor structure, internal consistency, reproducibility, construct validity, and ability to detect change.ResultsThis study supports the IBS-QOL as a psychometrically valid measure. Factor analyses suggested that IBS-specific QOL as measured by the IBS-QOL is a unidimensional construct. Construct validity was further buttressed by significant correlations between IBS-QOL total scores and related measures of IBS-d severity including the historically-relevant Irritable Bowel Syndrome Adequate Relief (IBS-AR) item and the FDA’s Clinical Responder definition. The IBS-QOL also showed a significant ability to detect change as evidenced by analysis of treatment effects. A minority of the items, unrelated to the IBS-d, performed less well by the standards set by the original authors.ConclusionsWe established that the IBS-QOL total score is a psychometrically valid measure of HRQOL in IBS-d patients enrolled in this study. Our analyses suggest that the IBS-QOL items demonstrate very good construct validity and ability to detect changes due to treatment effects. Furthermore, our analyses suggest that the IBS-QOL items measure a univariate construct and we believe further modeling of the IBS-QOL from an item response theory (IRT) approach under both non-treatment and treatment conditions would greatly further our understanding as item-based methods could be used to develop a short form.

Integrated decision making model for urban disaster management: A multi-objective genetic algorithm approach

Article history: Received June 2 2013 Received in revised format August 15 2013 Accepted August 15 2013 Available online August 31 2013 In recent decays, there has been an extensive improvement in technology and knowledge; hence, human societies have started to fortify their urban environment against the natural disasters in order to diminish the context of vulnerability. Local administrators as well as government officials are thinking about new options for disaster management programs within their territories. Planning to set up local disaster management facilities and stock pre-positioning of relief items can keep an urban area prepared for a natural disaster. In this paper, based on a realworld case study for a municipal district in Tehran, a multi-objective mathematical model is developed for the location-distribution problem. The proposed model considers the role of demand in an urban area, which might be affected by neighbor wards. Integrating decisionmaking process for a disaster helps to improve a better relief operation during response phase of disaster management cycle. In the proposed approach, a proactive damage estimation method is used to estimate demands for the district based on worst-case scenario of earthquake in Tehran. Since such model is designed for an entire urban district, it is considered to be a large-scale mixed integer problem and hence, a genetic algorithm is developed to solve the model. © 2013 Growing Science Ltd. All rights reserved

Effects of Natural Disaster Trends: A Case Study for Expanding the Pre-Positioning Network of CARE International

The increasing number of natural disasters in the last decade necessitates the increase in capacity and agility while delivering humanitarian relief. A common logistics strategy used by humanitarian organizations to respond this need is the establishment of pre-positioning warehouse networks. In the pre-positioning strategy, critical relief inventories are located near the regions at which they will be needed in advance of the onset of the disaster. Therefore, pre-positioning reduces the response time by totally or partially eliminating the procurement phase and increasing the availability of relief items just after the disaster strikes. Once the pre-positioning warehouse locations are decided and warehouses on those locations become operational, they will be in use for a long time. Therefore, the chosen locations should be robust enough to enable extensions, and to cope with changing trends in disaster types, locations and magnitudes. In this study, we analyze the effects of natural disaster trends on the expansion plan of pre-positioning warehouse network implemented by CARE International. We utilize a facility location model to identify the additional warehouse location(s) for relief items to be stored as an extension of the current warehouse network operated by CARE International, considering changing natural disaster trends observed over the past three decades.

Emergency Relief Item Allocation Model Based on Grouping Disaster Spots

Emergency Relief Item Allocation Model Based on Grouping Disaster Spots

Location of temporary depots to facilitate relief operations after an earthquake

The type of humanitarian logistics problem of interest is an earthquake with significant damage, prioritized items for delivery, and an extensive time period over which supplies need to be delivered. The problem of interest is an outgrowth of a recent paper by [10], where they focused on supplying relief items from a central depot for a prolonged period of time. The drawback of their approach is that long travel distances of vehicles are required between demand points and the central depot. In this paper, we propose the location of temporary depots around the disaster-affected area, along with the required vehicles and resources, to improve logistical efficiency. A two-phase heuristic approach is proposed; it locates temporary depots and allocates covered demand points to an open depot in Phase I, and explores the best logistics performance under the given solution from Phase I in Phase II. Results from computational experiments and an earthquake case study are used to illustrate the benefits of this approach.

Using Seasonal Climate Forecasts to Guide Disaster Management: The Red Cross Experience during the 2008 West Africa Floods

In 2008, the seasonal forecast issued at the Seasonal Climate Outlook Forum for West Africa (PRESAO) announced a high risk of above-normal rainfall for the July–September rainy season. With probabilities for above-normal rainfall of 0.45, this forecast indicated noteworthy increases in the risk of heavy rainfall. When this information reached the International Federation of Red Cross and Red Crescent Societies (IFRC) West and Central Africa Office, it led to significant changes in the organization’s flood response operations. The IFRC regional office requested funds in advance of anticipated floods, prepositioned disaster relief items in strategic locations across West Africa to benefit up to 9,500 families, updated its flood contingency plans, and alerted vulnerable communities and decision-makers across the region. This forecast-based preparedness resulted in a decrease in the number of lives, property, and livelihoods lost to floods, compared to just one year prior in 2007 when similar floods claimed above 300 lives in the region. This article demonstrates how a science-based early warning informed decisions and saved lives by triggering action in anticipation of forecast events. It analyses what it took to move decision-makers to action, based on seasonal climate information, and to overcome traditional barriers to the uptake of seasonal climate information in the region, providing evidence that these barriers can be overcome. While some institutional, communication and technical barriers were addressed in 2008, many challenges remain. Scientists and humanitarians need to build more common ground.

A two-echelon stochastic facility location model for humanitarian relief logistics

We develop a two-stage stochastic programming model for a humanitarian relief logistics problem where decisions are made for pre- and post-disaster rescue centers, the amount of relief items to be stocked at the pre-disaster rescue centers, the amount of relief item flows at each echelon, and the amount of relief item shortage. The objective is to minimize the total cost of facility location, inventory holding, transportation and shortage. The deterministic equivalent of the model is formulated as a mixed-integer linear programming model and solved by a heuristic method based on Lagrangean relaxation. Results on randomly generated test instances show that the proposed solution method exhibits good performance up to 25 scenarios. We also validate our model by calculating the value of the stochastic solution and the expected value of perfect information.

A transshipment model for distribution and inventory relocation under uncertainty in humanitarian operations

The number of disasters and humanitarian crises which trigger humanitarian operations is ever-expanding. Unforeseen incidents frequently occur in the aftermath of a disaster, when humanitarian organizations are already in action. These incidents can lead to sudden changes in demand. As fast delivery of relief items to the affected regions is crucial, the obvious reaction would be to deliver them from neighbouring regions. Yet, this may incur future shortages in those regions as well. Hence, an integrated relocation and distribution planning approach is required, considering current demand and possible future developments. For this situation, a mixed-integer programming model is developed containing two objectives: minimization of unsatisfied demand and minimization of operational costs. The model is solved by a rolling horizon solution method. To model uncertainty, demand is split into certain demand which is known, and uncertain demand which occurs with a specific probability. Periodically increasing penalty costs are introduced for the unsatisfied certain and uncertain demand. A sensitivity analysis of the penalty costs for unsatisfied uncertain demand is accomplished to study the trade-off between demand satisfaction and logistical costs. The results for an example case show that unsatisfied demand can be significantly reduced, while operational costs increase only slightly.

Special issue on optimization in disaster relief

It has been a real pleasure to edit this special issue. It is quite timely given that this area has gained substantial momentum lately. Part of this is due to some recent and very spectacular large disasters. However, another explanation is that researchers realize that the world has become much more interdependent and subject to risk and therefore studying disasters also brings new insights into better understanding regular supply chain management subject to increased volatility. We received a large number of applications from which we selected the 15 papers in this issue. We are pleased to note that many submissions were related to real applications or at least showed a real concern for applicability of the results. Unfortunately, we had to turn down a number of good submissions. Some because they did not have a clear enough link with the subject and hence we were not sure about the applicability or relevance of the work to humanitarian operations. A few papers that did not make it to this issue will be published in later regular issues of the journal. The selection of papers in this issue is very rich and showcases the large variety of challenging research questions related to disaster management. Topics range from forecasting of the impact of disasters and the resulting needs for support, to reliability and repair of disaster supply chains, prepositioning of relief items, inventory and other scarce resource allocation, evacuation of victims, pandemics modeling and more general frameworks for system design. The richness and variety of topics

Inventory relocation for overlapping disaster settings in humanitarian operations

The number and scale of humanitarian operations has significantly increased during the past decades due to the rising number of humanitarian emergencies and natural disasters worldwide. Therefore, the development of appropriate planning methods for optimization of the respective supply chains is constantly growing in importance. A specific problem in the context of humanitarian operations is the supply of relief items to the affected areas after the occurrence of a sudden change in demand or supply, for example, due to an epidemic or to unexpected shortages, during an ongoing humanitarian action. When such overlapping disasters occur, goods must be relocated to existing depots in a way which enables rapid supply to regions with new and urgent demand. At the same time, ongoing operations have to continue, i.e., the other regions should not suffer from shortages, and possible future emergencies must be taken into account. This is a planning situation under uncertainty as it is not known in advance if and where a disruption--and hence additional demand--will occur. In this paper, an optimization model for such situations is developed based on penalty costs for non-satisfied demand. A rolling horizon approach for solving the model is presented, and it is shown that taking into account the possibility of future disruptions can help to balance inventories and to reduce total non-served demand.

Pre-Positioning of Emergency Items for CARE International

Each year, about 500 natural disasters kill approximately 70,000 people and affect more than 200 million people worldwide. In the aftermath of such events, large quantities of supplies are needed to provide relief aid to the affected. CARE International is one of the largest humanitarian organizations that provide relief aid to disaster survivors. The most vital issues in disaster response are agility in mobilizing supplies and effectiveness in distributing them. To improve disaster response, a research group from Georgia Institute of Technology collaborated with CARE to develop a model to evaluate the effect that pre-positioning relief items would have on CARE's average relief-aid emergency response time. The model's results helped CARE managers to determine a desired configuration for the organization's pre-positioning network. Based on the results of our study and other factors, CARE has pre-positioned relief supplies in three facilities around the world.

Impact of the 26 December 2003 Bam Earthquake on Activities of Daily Living and Instrumental Activities of Daily Living of Older People

This study compares self-reported Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) status among elderly survivors of the 2003 Bam Earthquake before, two months after, and five years after the event, and explores related determinants. A two-stage cluster survey was conducted on 210 elderly survivors in the earthquake-stricken area five years after the event. Both ADL and IADL scores decreased two months after earthquake compared to prior status (p <0.001). No differences were observed between two months and five years after the event (p >0.05). Access to medical services were not related to level of ADL or IADL (p = 0.52 and p = 0.74, respectively). Elderly survivors with lower functional capability in terms of ADL experienced more problems in access to relief items (p = 0.04), but no similar association was found for IADL (p = 0.26). The Bam earthquake adversely affected functional capacity of the elderly. Disaster responders must take into account functional capacity of elders when planning for medical and relief operations.

Efficient stockpiling and shipping policies for humanitarian relief: UNHCR’s inventory challenge

The United Nations High Commissioner for Refugees (UNHCR) establishes and maintains refugee camps to meet the needs of 34.5 million people affected by disaster or war worldwide. Like other international humanitarian organizations, UNHCR maintains central stockpiles which supply these refugee operations. Management at UNHCR seeks to improve the timeliness and quality of its disaster response subject to its budget constraints. We develop an inventory model to analyze the interaction between a stockpile and a downstream refugee camp or relief operation. We consider two inventory decisions: first, how to partition a fixed budget between stockpiling and shipping costs in order to best meet the needs of beneficiaries; and second, given the shipping budget determined by the budget partition, how to ship relief items from the stockpile to a downstream relief operation in an efficient manner. We solve for the shipment policy using dynamic programming, then determine the optimal stockpile size given knowledge of the optimal shipment policy. The optimization balances a key tradeoff: a larger stockpile is costly to procure and maintain, but enhances a humanitarian organization's ability to respond to relief operation demands. We provide insights into shipment strategies and stockpile size. We also develop a spreadsheet model to help humanitarian organizations in their operational decision-making, leading to improved response to beneficiaries. Humanitarian organizations must use their financial resources wisely to carry out their mandates, and models of this type can help them make the best use of their limited response resources.