Relief distribution networks : a systematic review

In the last 20 years, Emergency Management has received increasing attention from the scientific community. Meanwhile, the study of relief distribution networks has become one of the most popular topics within the Emergency Management field. In fact, the number and variety of contributions devoted to the design or the management of relief distribution networks has exploded in the recent years, motivating the need for a structured and systematic analysis of the works on this specific topic. To this end, this paper presents a systematic review of contributions on relief distribution networks in response to disasters. Through a systematic and scientific methodology, it gathers and consolidates the published research works in a transparent and objective way. It pursues three goals. First, to conduct an up-to-date survey of the research in relief distribution networks focusing on the logistics aspects of the problem, which despite the number of previous reviews has been overlooked in the past. Second, to highlight the trends and the most promising challenges in the modeling and resolution approaches and, finally, to identify future research perspectives that need to be explored

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

International audienceIn 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, 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

Dynamic Relief Items Distribution Model with Sliding Time Window in the Post-Disaster Environment

In smart cities, relief items distribution is a complex task due to the factors such as incomplete information, unpredictable exact demand, lack of resources, and causality levels, to name a few. With the development of Internet of Things (IoT) technologies, dynamic data update provides the scope of distribution schedule to adopt changes with updates. Therefore, the dynamic relief items distribution schedule becomes a need to generate humanitarian supply chain schedules as a smart city application. To address the disaster data updates in different time periods, a dynamic optimised model with a sliding time window is proposed that defines the distribution schedule of relief items from multiple supply points to different disaster regions. The proposed model not only considers the details of available resources dynamically but also introduces disaster region priority along with transportation routes information updates for each scheduling time slot. Such an integrated optimised model delivers an effective distribution schedule to start with and updates it for each time slot. A set of numerical case studies is formulated to evaluate the performance of the optimised scheduling. The dynamic updates on the relief item demands’ travel path, causality level and available resources parameters have been included as performance measures for optimising the distributing schedule. The models have been evaluated based on performance measures to reflect disaster scenarios. Evaluation of the proposed models in comparison to the other perspective static and dynamic relief items distribution models shows that adopting dynamic updates in the distribution model cover most of the major aspects of the relief items distribution task in a more realistic way for post-disaster relief management. The analysis has also shown that the proposed model has the adaptability to address the changing demand and resources availability along with disaster conditions. In addition, this model will also help the decision-makers to plan the post-disaster relief operations in more effective ways by covering the updates on disaster data in each time period

A Multi-Criteria Vertical Coordination Framework for a Reliable Aid Distribution

Purpose: This study proposes a methodology that translates multiple humanitarian supply chain stakeholders’ preferences from qualitative to quantitative values, enabling these preferences to be integrated into optimization models to ensure their balanced and simultaneous implementation during the decision-making process. Design/methodology/approach: An extensive literature review is used to justify the importance of developing a strategy that minimizes the impact of a lack of coordination on humanitarian logistics decisions. A methodology for a multi-criteria framework is presented that allows humanitarian stakeholders’ interests to be integrated into the humanitarian decisionmaking process. Findings: The findings suggest that integrating stakeholders’ interests into the humanitarian decision-making process will improve its reliability. Research limitations/implications: To further validate the weights of each stakeholder’s interests obtained from the literature review requires interviews with the corresponding organizations. However, the literature review supports the statements in this paper. Practical implications: The cost of a lack of coordination between stakeholders in humanitarian logistics has been increasing during the last decade. These coordination costs can be minimized if humanitarian logistics’ decision-makers measure and simultaneously consider multiple stakeholders’ preferences. Social implications: When stakeholders’ goals are aligned, the humanitarian logistics response becomes more efficient, increasing the quality of delivered aid and providing timely assistance to the affected population in order to minimize their suffering. Originality/value: This study provides a methodology that translates humanitarian supply chain stakeholders’ interests into quantitative values, enabling them to be integrated into mathematical models to ensure relief distribution based on the stakeholders’ preferences.Peer Reviewe

The SNS logistics network design : location and vehicle routing.

Large-scale emergencies caused by earthquake, tornado, pandemic flu, terrorism attacks and so on can wreak havoc to communities. In order to mitigate the impact of the events, emergency stockpiles of food, water, medicine and other materials have been set up around the US to be delivered to the affected areas during relief operations. One type of stockpile is called the Strategic National Stockpile (SNS). The SNS logistics network is designed to have multiple stages of facilities, each of which is managed by different levels of governmental authorities - federal, state and local authorities. The design of a logistics network for delivery of the SNS materials within a state are explored in this dissertation. There are three major areas of focus in this dissertation: (1) the SNS facility location model, which is used to determine sites for locating Receiving, Staging and Storage (RSS) and Regional Distribution Nodes (RDNs) to form a logistics network to deliver relief material to Points of Demand (PODs), where the materials are directly delivered to the affected population; (2) the SNS Vehicle Routing Problem (VRP), which is used to assist the SNS staff in determining the numbers of various types of trucks, and the routing schedules of each truck to develop an operational plan for delivering the required relief materials to the assigned PODs within the required duration; (3) the location-routing analysis of emergency scenarios, in which the facility location model and the VRP solution are integrated through the use of a computer program to run on several assumed emergency scenarios. Using real data from the department of public health in the Commonwealth of Kentucky, a transshipment and location model is formulated to determine the facility locations and the transshipment quantities of materials; a multiple-vehicle routing model allowing split deliveries and multiple routes per vehicle that must be completed within a required duration is formulated to determine the routing and scheduling of trucks. The facility location model is implemented using Microsoft Solver Foundation and C#. An algorithm combining the Clark and Wright saving algorithm and Simulated Annealing is designed and implemented in C# to solve the VRP. The algorithm can determine whether there is shortage of transportation capacity, and if so, how many of various types of trucks should be added for optimal performance. All the solution algorithms are integrated into a web-based SNS planning tool. In the location-routing analysis of emergency scenarios, a binary location model and an algorithm for solving VRP solution are integrated as a computer program to forecast the feasibility of distribution plans and the numbers of required trucks of various types. The model also compares the costs and benefits of direct and indirect shipment. A large-scale emergency scenario in which a specific type of vaccine is required to be delivered to the entire state of Kentucky is considered. The experiments are designed based on the real data provided by the Kentucky state government. Thus the experimental results provide valuable suggestions for future SNS preparedness planning

An exact solution approach for multi-objective location-transportation problem for disaster response

This paper considers a three-objective location–transportation problem for disaster response. The location problem aims at determining the number, the position and the mission of required humanitarian aid distribution centers (HADC) within the disaster region. The transportation problem deals with the distribution of aid from HADCs to demand points. Three conflicting objectives are considered. The first objective minimizes the total transportation duration of needed products from the distribution centers to the demand points. The second objective minimizes the number of agents (first-aiders) needed to open and operate the selected distribution centers. The third objective minimizes the non-covered demand for all demand points within the affected area. We propose an epsilon-constraint method for this problem and prove that it generates the exact Pareto front. The proposed algorithm can be applied to any three-objective optimization problem provided that the problem involves at least two integer and conflicting objectives. The results obtained in our experimental study show that the computing time required by the pr oposed method may be large for some instances. A heuristic version of our algorithm yielded, however, good approximation of the Pareto front in relatively short computing times.Keywords: Emergency response; Location–transportation problems; Multi-objective combinatorial optimization; Exact method; Epsilon-constraint method

Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review

In the past decade the humanitarian supply chain (HSC) has attracted the attention of researchers due to the increasing frequency of disasters. The uncertainty in time, location, and severity of disaster during predisaster phase and poor conditions of available infrastructure during postdisaster phase make HSC operations difficult to handle. In order to overcome the difficulties during these phases, we need to assure that HSC operations are designed in an efficient manner to minimize human and economic losses. In the recent times, several mathematical optimization techniques and algorithms have been developed to increase the efficiency of HSC operations. These techniques and algorithms developed for the field of HSC motivate the need of a systematic literature review. Owing to the importance of mathematical modelling techniques, this paper presents the review of the mathematical contributions made in the last decade in the field of HSC. A systematic literature review methodology is used for this paper due to its transparent procedure. There are two objectives of this study: the first one is to conduct an up-to-date survey of mathematical models developed in HSC area and the second one is to highlight the potential research areas which require attention of the researchers

OR models in urban service facility location : a critical review of applications and future developments

[EN] Facility location models are well established in various application areas with more than a century of history in academia. Since the 1970s the trend has been shifting from manufacturing to service industries. Due to their nature, service industries are frequently located in or near urban areas that results in additional assumptions, objectives and constraints other than those in more traditional manufacturing location models. This survey focuses on the location of service facilities in urban areas. We studied 110 research papers across different journals and disciplines. We have analyzed these papers on two levels. On the first, we take an Operations Research perspective to investigate the papers in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. On the second level, we compare and contrast the papers in each of these applications categories: (a) Waste management systems (WMS), (b) Large-scale disaster (LSD), (c) Small-scale emergency (SSE), (d) General service and infrastructure (GSI), (e) Non-emergency healthcare systems (NEH) and (f) Transportation systems and their infrastructure (TSI). Each of these categories is critically analyzed in terms of application, assumptions, decision variables, input parameters, constraints, objective functions and solution techniques. Gaps, research opportunities and trends are identified within each category. Finally, some general lessons learned based on the practicality of the models is synthesized to suggest avenues of future research.Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards (No. DPI2015-65895-R) financed by FEDER funds.Farahani, RZ.; Fallah, S.; Ruiz García, R.; Hosseini, S.; Asgari, N. (2019). OR Models in Urban Service Facility Location: A Critical Review of Applications and Future Developments. European Journal of Operational Research. 276(1):1-27. https://doi.org/10.1016/j.ejor.2018.07.036S127276

Planification de la distribution en contextes de déploiement d'urgence et de logistique hospitalière

L’optimisation de la distribution est une préoccupation centrale dans l’amélioration de la performance des systèmes industriels et des entreprises de services. Avec les avancées technologiques et l’évolution du monde des affaires, de nouveaux domaines d’application posent des défis aux gestionnaires. Évidemment, ces problèmes de distribution deviennent aussi des centres d’intérêt pour les chercheurs. Cette thèse étudie l’application des méthodes de recherche opérationnelle (R.O.) à l’optimisation des chaînes logistiques dans deux contextes précis : le déploiement logistique en situation d’urgence et la logistique hospitalière. Ces contextes particuliers constituent deux domaines en forte croissance présentant des d’impacts majeurs sur la population. Ils sont des contextes de distribution complexes et difficiles qui exigent une approche scientifique rigoureuse afin d’obtenir de bons résultats et, ultimement, garantir le bien-être de la communauté. Les contributions de cette thèse se rapportent à ces deux domaines. D’abord, nous présentons une révision systématique de la littérature sur le déploiement logistique en situation d’urgence (Chapitre 2) qui nous permet de consolider et de classifier les travaux les plus importants du domaine ainsi que d’identifier les lacunes dans les propositions actuelles. Cette analyse supporte notre seconde contribution où nous proposons et évaluons trois modèles pour la conception d’un réseau logistique pour une distribution juste de l’aide (Chapitre 3). Les modèles cherchent à assurer une distribution équitable de l’aide entre les points de demande ainsi qu’une stabilité dans le temps. Ces modèles permettent les arrérages de la demande et adaptent l’offre aux besoins de façon plus flexible et réaliste. Le deuxième axe de recherche découle d’un mandat de recherche avec le Ministère de la Santé et de Services sociaux du Québec (MSSS). En collaboration avec les gestionnaires du système de santé québécois, nous avons abordé la problématique du transport d’échantillons biomédicaux. Nous proposons deux modèles d’optimisation et une approche de résolution simple pour résoudre ce problème difficile de collecte d’échantillons (Chapitre 4). Cette contribution est par la suite généralisée avec la synchronisation des horaires d’ouverture de centres de prélèvement lors de la planification des tournées. Une procédure itérative de recherche locale est proposée pour résoudre le problème (Chapitre 5). Il en découle un outil efficace pour la planification des tournées de véhicules dans le réseau des laboratoires québécois.Optimisation in distribution is a major concern towards the performance’s improvement of manufacturing and service industries. Together with the evolution of the business’ world and technology advancements, new practical challenges need to be faced by managers. These challenges are thus a point of interest to researchers. This thesis concentrates on the application of operational research (O.R.) techniques to optimise supply chains in two precise contexts: relief distribution and healthcare logistics. These two research domains have grown a lot recently and have major impacts on the population. These are two complex and difficult distribution settings that require a scientific approach to improve their performance and thus warrant the welfare among the population. This thesis’s contributions relate to those two axes. First, we present a systematic review of the available literature in relief distribution (Chapter 2) to consolidate and classify the most important works in the field, as well as to identify the research’s gaps in the current propositions and approaches. This analysis inspires and supports our second contribution. In Chapter 3, we present and evaluate three models to optimise the design of relief distribution networks oriented to fairness in distribution. The models seek to ensure an equitable distribution between the points of demand and in a stable fashion in time. In addition, the models allow the backorder of demand to offer a more realistic and flexible distribution plan. The second research context result from a request from Quebec’s Ministry of Health and Social Services (Ministère de la Santé et des Services sociaux – MSSS). In partnership with the managers of Quebec’s healthcare system, we propose an approach to tackle the biomedical sample transportation problem faced by the laboratories’ network in Quebec’s province. We propose two mathematical formulations and some fast heuristics to solve the problem (Chapter 4). This contribution is later extended to include the opening hours’ synchronisation for the specimen collection centers and the number and frequency of pick-ups. We propose an iterated local search procedure (ILS) to find a routing plan minimising total billable hours (Chapter 5). This leads to an efficient tool to routing planning in the medical laboratories’ network in Quebec