Decision making in humanitarian logistics - A multi-objective optimization model for relocating relief goods during disaster recovery operations

ABSTRACT Disaster recovery operations rarely proceed smoothly and disruptions often require the redistribution of relief items. Such a redistribution has to be carried out taking into account both the current disruption and the uncertainty regarding possible future incidents in the respective area. As decisions have to be made fast in humanitarian operations, extensive optimization runs cannot be conducted in such a situation. Nevertheless, sensible decisions should be made to ensure an efficient redistribution, considering not only satisfaction of needs but also operational costs, as the budget is usually scarce in the recovery phase of a disaster. In this work, different scenarios are generated and then solved with a multiobjective optimization model to explore possible developments. By evaluating the results of these scenarios, decision rules are identified which can support the decision maker in the actual disaster situation in making fast, but nevertheless well-founded, decisions

Facility location optimization model for emergency humanitarian logistics

Since the 1950s, the number of natural and man-made disasters has increased exponentially and the facility location problem has become the preferred approach for dealing with emergency humanitarian logistical problems. To deal with this challenge, an exact algorithm and a heuristic algorithm have been combined as the main approach to solving this problem. Owing to the importance that an exact algorithm holds with regard to enhancing emergency humanitarian logistical facility location problems, this paper aims to conduct a survey on the facility location problems that are related to emergency humanitarian logistics based on both data modeling types and problem types and to examine the pre- and post-disaster situations with respect to facility location, such as the location of distribution centers, warehouses, shelters, debris removal sites and medical centers. The survey will examine the four main problems highlighted in the literature review: deterministic facility location problems, dynamic facility location problems, stochastic facility location problems, and robust facility location problems. For each problem, facility location type, data modeling type, disaster type, decisions, objectives, constraints, and solution methods will be evaluated and real-world applications and case studies will then be presented. Finally, research gaps will be identified and be addressed in further research studies to develop more effective disaster relief operations

Making decisions for effective humanitarian actions: a conceptual framework for relief distribution

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Assessing Requirements for Decision Support Systems in Humanitarian Operations

Efficient and effective decision making in the chaotic environment of humanitarian relief distribution (HRD) is a challenging task. Decision makers, in such situations, are required to concentrate on numerous attributes classified by three decision factors: objectives, variables, and constraints. Recent HRD literature mainly focuses on optimizing procedures while neglecting the quantification of influential requirements (factors) for information systems to provide decision-making support. This article addresses this gap by accumulating those affecting attributes from the literature. It investigates their practical implications in HRD by measuring the preferences of a Delphi panel of 23 experts. The results quantify the importance of each attribute – along with the newly added ones by the experts – in the proposed process model for HRD in a large-scale sudden onset. Our work provides future researchers not only with a comprehensive set of practically feasible decision-making factors in HRD but also with an understanding of their influences or correlations

Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty : A System Design Approach

With respect to copyright, all the papers were excluded from the dissertation.Disasters threaten society with widespread destruction of infrastructure and livelihood. For their survival, affected inhabitants depend on immediate humanitarian assistance from diverse organizations. During quick responses, humanitarian decision- makers (HDMs) act rapidly to distribute necessary relief goods, despite the deep, prevailing uncertainty that arises from scarce, conflicting, and uncertain information. To support HDMs in humanitarian relief distribution (HRD) decision-making, humanitarian logistics (HL) researchers have developed various mathematical models. These models are, however, specific to disaster scenarios, and most of them are detached from the realities of the field since end-users (mainly practitioners) have been absent in the development process. When tested, these decision-making models were found to be capable of producing good results, but they have not been implemented in practice because of operational inconsistency or complexity (i.e., lack of user-friendliness). Therefore, humanitarian responders are still in need of support systems to assist them in determining effective HRD. A computer-based decision support system (DSS) can fill this need by providing necessary recommendations and suggesting decision alternatives. Hence, developing such DSSs is always the priority in HL.publishedVersio

Logística humanitária : uma revisão bibliográfica

Orientador : Prof. Dr. Guilherme F. FredericoMonografia (especialização) - Universidade Federal do Paraná, Curso de MBA em Gerência de Sistemas LogísticosInclui referênciasResumo : A logística humanitária é um tema que vem ganhando destaque entre as publicações acadêmicas visto o crescente número de desastres ocorrendo ao redor do mundo. Ela difere em diversos aspectos da logística comercial, principalmente porque lida não apenas com transações de produtos e serviços, mas também com o impacto no ser humano. Da mesma forma, diversos outros fatores devem ser considerados, como a instabilidade e riscos variáveis. Este trabalho irá expor uma seleção de trabalhos acadêmicos voltados ao assunto que apresentam um problema específico na rede logística em relação a ocorrência de desastres. O objetivo deste trabalho é analisar, através de critérios selecionados, as tendências acadêmicas, bem como verificar necessidades e apontar direcionamentos para novos estudos

A MATHEMATICAL FRAMEWORK FOR OPTIMIZING DISASTER RELIEF LOGISTICS

In today's society that disasters seem to be striking all corners of the globe, the importance of emergency management is undeniable. Much human loss and unnecessary destruction of infrastructure can be avoided with better planning and foresight. When a disaster strikes, various aid organizations often face significant problems of transporting large amounts of many different commodities including food, clothing, medicine, medical supplies, machinery, and personnel from several points of origin to a number of destinations in the disaster areas. The transportation of supplies and relief personnel must be done quickly and efficiently to maximize the survival rate of the affected population. The goal of this research is to develop a comprehensive model that describes the integrated logistics operations in response to natural disasters at the operational level. The proposed mathematical model integrates three main components. First, it controls the flow of several relief commodities from sources through the supply chain until they are delivered to the hands of recipients. Second, it considers a large-scale unconventional vehicle routing problem with mixed pickup and delivery schedules for multiple transportation modes. And third, following FEMA's complex logistics structure, a special facility location problem is considered that involves four layers of temporary facilities at the federal and state levels. Such integrated model provides the opportunity for a centralized operation plan that can effectively eliminate delays and assign the limited resources in a way that is optimal for the entire system. The proposed model is a large-scale mixed integer program. To solve the model, two sets of heuristic algorithms are proposed. For solving the multi-echelon facility location problem, four heuristic approaches are proposed. Also four heuristic algorithms are proposed to solve the general integer vehicle routing problem. Overall, the proposed heuristics could efficiently find optimal or near optimal solution in minutes of CPU time where solving the same problems with a commercial solver needed hours of computation time. Numerical case studies and extensive sensitivity analysis are conducted to evaluate the properties of the model and solution algorithms. The numerical analysis indicated the capabilities of the model to handle large-scale relief operations with adequate details. Solution algorithms were tested for several random generated cases and showed robustness in solution quality as well as computation time

GIS and optimisation:potential benefits for emergency facility location in humanitarian logistics

Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics

Leveraging Logistics Partnerships: Lessons from Humanitarian Organizations

This thesis explores an under-researched field: humanitarian organizations and their supply chains. Humanitarian organizations respond to the basic needs of populations that experience a tragic disruption in their lives. Given the challenging contexts they operate in, this thesis first explores the factors that contribute to their performance. Thereafter, it identifies the strategies and organizational structures they need to adopt to respond to the growing challenge of attending to more people with fewer resources. It argues that to excel in disaster preparedness and response, among other things, humanitarian organizations need to engage in at least three partnership arrangements – temporary supply networks, a logistics coordination platform and a series of business and CSO partnerships – and build and strengthen a number of related capabilities. The invisible resource that once leveraged increases the opportunity and ability of a humanitarian organization to perform better is its social capital with parties involved in these partnership arrangements. In terms of lessons for business, it verifies the relevance and benefits of humanitarian partnership structures to commercial supply chains in specific scenarios. Apart from holding some lessons for humanitarian organizations themselves, this thesis contributes to the virtual organizing literature and provides empirical evidence for the emergence and management of logistics virtual organizations

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management