Humanitarian logistics is an emerging phenomenon which have been increasingly recognized due to the increase of disasters, where little is still known about the role of companies operating in the private sector for this phenomenon. Furthermore, it is assumed that both natural and man-made disasters will increase in both the occurrence and the effect in the future, which enforces the need for practices and theories to deal with them more effectively. There were 1438 epidemic outbreaks between 2010-2018 according to the World Health Organization. During the COVID-19 pandemic shortages in the medical sector were evident, which had disastrous effects. During these difficult times companies from the private sector implemented drastic production changes to supply the disinfectant, hand sanitizers, and protective personal equipment that was missing. The purpose of this thesis is to investigate how Swedish firms have implemented/ enabled drastic production change in case of humanitarian logistics during COVID-19, for the previously mentioned product types. Sweden was chosen as the empirical setting, as many contributions could be seen amongst the Swedish private companies, where the data collection was done with eight respondents in eight different companies being in multiple industries. By using a qualitative grounded theory approach, the findings suggest that the drastic production change for the private companies in terms of humanitarian logistics is influenced by five different factors. Firstly, its dependent on developing a social motive, with and without economic benefits. Secondly, was coordinating between external and internal stakeholders. Thirdly, was coordinating amongst existing and acquired resources and capabilities. Fourthly, was coordinating product change to legal requirements. Finally, was coordinating and reacting to disruptions through alternative production. This study contributes to humanitarian logistics in several theoretical ways. Initially, it brings new insights specific for private firms in their implementation and enablement for drastic production change. Furthermore, it also extends the knowledge for the private sector and their involvement in humanitarian logistics. Additionally, it also extends the knowledge specific to products for companies within the private sector related to disaster relief in humanitarian operations. Subsequently, the study also contributes with findings from Sweden, which is an empirical setting that has not been researched within the area previously. Moreover, the study also has practical recommendations which might be useful for future crisis scenarios. Where it was evident that the involvement of private firms in humanitarian logistics was driven both by social and economic motives. Additionally, private firms should also be aware of their existing resources and capabilities which could enable an alternative production when society needs it the most. Lastly, firms should not be intimidated by regulation and production requirements, as there have been a common force among stakeholders to solve such issues.

Humanitarian relief and aid organizations all over the world implement efforts aimed at recovering from disasters, reducing poverty and promoting human rights. The purpose of this dissertation is to develop a series of quantitative decision models to help address some of the challenges faced by humanitarian logistics. The first study discusses the development of a spreadsheet-based multicriteria scheduling model for a small development aid organization in a South American developing country. Development aid organizations plan and execute efforts that are primarily directed towards promoting human welfare. Because these organizations rely heavily on the use of volunteers to carry out their social mission, it is important that they manage their volunteer workforce efficiently. In this study, we demonstrate not only how the proposed model helps to reduce the number of unfilled shifts and to decrease total scheduling costs, but also how it helps to better satisfy the volunteers’ scheduling preferences, thus supporting long-term retention and effectiveness of the workforce. The purpose of the second study is to develop a decision model to assist in the management of humanitarian relief volunteers. One of the challenges faced by humanitarian organizations is that there exist limited decision technologies that fit their needs while it has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. Even though employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this study, we discuss a series of principles from the field of volunteer management and develop a multicriteria optimization model to assist in the assignment of both individual volunteers and volunteer groups to tasks. We present illustrative examples and analyze two complementary solution methodologies that incorporate the decision maker's preferences and knowledge and allow him/her to trade-off conflicting objectives. The third study discusses the development of a decision model for the procurement of goods in humanitarian efforts. Despite the prevalence of procurement expenditures in humanitarian efforts, procurement in humanitarian contexts is a topic that has only been discussed in a qualitative manner in the literature. In our paper, we introduce a two stage decision model with recourse to improve the procurement of goods in humanitarian relief supply chains and present an illustrative example. Conclusions, limitations, and directions for future research are also discussed. / Ph. D.

Emergency managers are often faced with the toughest decisions that can ever be made, people's lives hang in the balance. Nevertheless, these tough decisions have to be made, and made quickly. There is usually too much information to process to make the best decisions. Decision support systems can relieve a significant amount of this onus, making decision while considering the complex interweaving of constraints and resources that define the boundary of the problem. We study these complex emergency management, approaching the problem with discrete optimization. Using our operational research knowledge to model mass casualty incidents, we seek to provide solutions and insights for the emergency managers. This dissertation proposes a novel deterministic model to optimize the casualty transportation and treatment decisions in response to a MCI. This deterministic model expands on current state of the art by; (1) including multiple dynamic resources that impact the various interconnected decisions, (2) further refining a survival function to measure expected survivors, (3) defining novel objective functions that consider competing priorities, including maximizing survivors and balancing equity, and finally (4) developing a MCI response simulation that provides insights to how optimization models could be used as decision-support mechanisms. / Doctor of Philosophy / Emergency managers are often faced with the toughest decisions that can ever be made, people's lives hang in the balance. Nevertheless, these tough decisions have to be made, and made quickly. But to make the best decisions, there is usually too much information to process. Computers and support tools can relieve a significant amount of this onus, making decision while considering the complex interweaving of constraints and resources that define the boundary of the problem. This dissertation provides a mathematical model that relates the important decisions made during a MCI response with the limited resources of the surrounding area. This mathematical model can be used to determine the best response decisions, such as where to send casualties and when to treat them. This model is also used to explore ideas of fairness and equity in casualty outcomes and examine what may lead in unfair response decisions. Finally, this dissertation uses a simulation to understand how this model could be used to not only plan the response, but also update the plan as you learn new information during the response roll-out.

[pt] Em janeiro de 2011, chuvas intensas e concentradas deflagraram inundações e deslizamentos atingindo sete cidades da Região Serrana do Rio de Janeiro, sendo considerado o maior desastre na história do país. Essa tragédia serviu de lição aprendida para mudanças no gerenciamento de riscos de desastres no Brasil. Este estudo inova ao pesquisar o impacto nas empresas da região afetada. A abordagem da logística humanitária – que tem por função adequar o fluxo de pessoas e materiais em tempo oportuno na cadeia de assistência às pessoas afetadas por desastres – se faz relevante para as empresas privadas visto que pode minimizar os impactos dos desastres e aumentar a resiliência nas cadeias de suprimentos. De acordo com o ciclo de gestão de desastres – mitigação, preparação, resposta e reconstrução – este estudo tem por objetivo avaliar como as empresas da Região Serrana do Rio de Janeiro foram impactadas no desastre de 2011 e como as empresas estão se preparando para evitar que novas situações de emergência afetem a sua operação. Baseado em um modelo de questionário, aplicado com sucesso em desastres na Nova Zelândia, realiza-se uma pesquisa de levantamento em empresas da região e dois estudos de caso. Os resultados obtidos apontam para a necessidade de maior planejamento das empresas face à recorrência desse tipo de evento nas cidades afetadas. / [en] In January 2011, intense and concentrated rain raised floods and slidings reaching seven cities of the mountain region of Rio de Janeiro, which is considered the biggest disaster ever happened in Brazil. This tragedy served as lessons learned for changes in the disasters risk management in the country. This study innovates in researching the impact on the private sector in the cities affected. Humanitarian logistics, which function is to adequate the flow of material and personal in time to relief operations, is relevant for private sector as it can minimize the impacts of disasters and develop resilience in supply chains. According to the disaster operations life cycle – mitigation, preparation, response and recovery – this study aims to evaluate how the private sector in the mountain region of Rio de Janeiro was impacted by the 2011 disaster and how businesses are getting prepared to avoid future emergence situations affect its operations. Based in a model questionnaire, successfully applied in disasters in New Zealand, a survey research is conducted in the private sector of the cities affected and two case studies are carried out. The findings of this research point to the need of planning in the private sector due to the recurrence of this kind of event in the mountain region of Rio de Janeiro.

Yes / For years, humankind has been facing various disasters of which logistics has a crucial role for alleviating sufferings of vulnerable people, who are isolated and in need of basic supplies. Owing to the increasing importance of logistics in humanitarian operations, logistics service providers (LSPs) have recently become more prominent. Yet, only a few LSPs have the capabilities and mechanisms to offer operational solutions for humanitarian relief. Also, the conducted extensive literature review makes evident that the existence of a limited number of normative research reveals a barrier about what LSPs can bring into the humanitarian field. Accordingly, why LSPs are particularly important in the humanitarian supply chain and how LSPs manage their activities and resources in humanitarian operations become the main questions to be addressed. Thus, this study seeks to explore humanitarian operations of LSPs from different dimensions, enabled by Business Model Canvas (BMC). In this sense, the obtained findings clarify both similar and different viewpoints of diverse LSPs when mapped against the BMC. Consequently, the categorised interrelated information presented through the cross-case synthesis provide novelty to advance insights both on strategic missions of LSPs in humanitarian relief operations and on the usage of BMC beyond its common commercial implementations.

This thesis focuses on developing a comprehensive framework for understanding the challenges NGOs face with in-kind donations in disaster relief. The overwhelming problem of inappropriate material donations, often referred to as the second disaster, has plagued disaster relief operations for decades now in both domestic and international disaster response. Despite efforts to promote ``cash only'' giving in disaster relief, unsolicited and mostly inappropriate in-kind giving continues to challenge NGOs in every major disaster. Researchers have identified this as one of the most pressing yet understudied challenges in disaster relief to date. This thesis is divided into three parts. In the first part, we conduct a multidisciplinary literature review from philanthropy, economics, public policy, corporate philanthropy and corporate social responsibility to understand why donors donate in-kind and why NGOs accept those donations. We describe the roles of the various players involved and explain the structure of the distribution channels in-kind donations follow both in disaster and non-disaster contexts. We then explain the challenges NGOs and their donors face with in-kind donations in the context of these channels. We identify systemic issues in the distribution channels and highlight current policies and practices that contribute to the second disaster. In the second part of this thesis, we propose a comprehensive framework to help donors, NGOs and policy makers comprehend the scope of the problem and identify strategies to address the challenge of unsolicited donations in disaster relief. Our framework provides a succinct representation of the main issues and players involved in the process in a format that is simple to work with and easy to understand. It supports comprehension of the many related issues and can help NGOs and policy making bodies (e.g., FEMA, NVOAD, USAID) assess current strategies and devise new approaches and solution strategies. In the third part of the thesis, we exploit our framework to propose a tiered strategy consisting of a set of solutions ranging from decision tools to help NGOs better screen in-kind donation offers to entire new channels for more productive in-kind giving in disaster relief. Each of these solutions may deter only a small fraction of the inappropriate flows, but together they can dramatically diminish the problem. Our proposed NGO decision tools both allow quick screening of donation offers in disaster relief and provide a framework for strategic management of corporate in-kind donations in the long term. We also propose a ``retail donation model" which can transform a portion of the current stream of unwanted and unusable in-kind donations from individuals and community groups into a valuable source of needed relief supplies through an entirely new donation channel. We document a successful implementation of an on-line retail donation model in the 2012 Sandy response.

Este trabalho trata da logística envolvida em operações de resposta a desastres, com foco na entrega final de suprimentos destinados a ajudar vítimas. Seu propósito é investigar os objetivos pertinentes ao planejamento do transporte da carga e encontrar uma metodologia para definir estratégia que sirva à tomada de decisão em campo. Para tanto, primeiramente identifica-se os objetivos adotados em modelos de Pesquisa Operacional para a tarefa em questão, através da análise de conteúdo das publicações pertinentes. Então, a abordagem do Pensamento Focado em Valores é utilizada para estruturar o problema. Finalmente, o método Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) é empregado na construção de um modelo de Análise da Decisão Multicritério (ADM), com consulta a um profissional experiente da área humanitária e aproveitando a análise da literatura previamente realizada. Neste processo, são elaboradas e avaliadas seis alternativas para a tomada de decisão condizentes com os valores da comunidade humanitária. Os resultados obtidos mostram que existe incompatibilidade entre os critérios de desempenho identificados nas publicações existentes e os objetivos perseguidos pelo Tomador da Decisão (TD) real. De acordo com o modelo construído, o atendimento de prioridades e a manutenção da sustentabilidade da operação são os objetivos que devem ser levados em conta para planejar a entrega de carga em pós-desastre, sendo que o custo e a equidade da distribuição não devem ser considerados. Conclui-se que o método adotado é útil à definição destes critérios e também ao desenvolvimento de estratégias que resultem em distribuições de ajuda melhores, aos olhos do próprio TD. Desta forma, ressalta-se que este trabalho contribui à área da Logística Humanitária com a investigação dos objetivos, assim como ao campo da ADM pela formalização dos processos de elaboração de alternativas, além da adição de mais uma aplicação possível ao repertório do método SMARTER. / This study concerns the logistics of disaster response operations, with a focus on final delivery of supplies to victims. The objectives here are to investigate what objectives are pertinent to the transportation-planning task and to find a methodology for choosing a strategy that aids decision-making on the field. For achieving these, a content analysis of Operations Research models is done, allowing the identification of such objectives, from which the problem is structured using a Value-Focused Thinking approach. Subsequently, the Simple Multi-Attribute Rating Exploiting Ranks (SMARTER) is employed to build a Multi-Criteria Decision Analysis (MCDA) model, consulting an experienced humanitarian professional and taking into account the results from the previous analysis. Throughout this process, six alternatives for making decisions are designed and evaluated based on the objectives defined. Findings are that there is incompatibility between performance criteria identified in the literature and objectives pursued by a real Decision Maker (DM). From the model presented by this thesis, one concludes that satisfying priorities and sustaining the response operation are the objectives to be taken into account when drawing an aid distribution plan. It also follows that the methodology adopted here is useful to defining such performance criteria and to develop strategies that result in better outcomes, as judged by the DM. Therefore, this study contributes to Humanitarian Logistics research area by casting a light on the objectives of a post-disaster task, and to the MCDA field by formalizing the process of designing alternatives for complex problems, besides adding a new application of SMARTER to its repertory.

[pt] Neste trabalho estudamos uma classe de problemas de otimização estocástica com incertezas endógenas que é formulado como um problema de programação não-linear inteira (MINLP). Esta classe de problemas difere dos problemas de otimização estocástica geralmente estudados na literatura pelo fato de que que a distribuição de probabilidade dos parâmetros aleatórios depende das decisões tomadas. Apesar de discutido dentro do contexto do problema de logística humanitária, a metodologia proposta e os resutados obtidos são válidos para uma classe geral de problemas que agrega uma variedade de aplicações. Em particular, propõe-se (i) uma técnica de convexificação de polinômios de variáveis binárias, (ii) um algoritmo de geração de cortes e (iii) a incorporação dos conceitos de importance sampling dentro do contexto de otimização estocástica de modo a permitir a solução de grandes instâncias do problema. Os resultados computacionais apresentados demonstram as vantagens da metodologia proposta ao permitir a solução de instâncias significativamente maiores que aquelas atualmente apresentadas em trabalhos relacionados. / [en] In this work we study a class of stochastic programming problems with endogenous uncertainty – i.e., those in which the probability distribution of the random parameters is decision-dependent – which is formulated as a mixed integer non-linear programming (MINLP) problem. Although discussed in the context of the humanitarian logistics problem, the proposed methodology and obtained results are also valid for a more general class of problems which comprehends a variety of applications. In particular, we propose (i) a convexification technique for polynomials of binary variables, (ii) an efficient cutgeneration algorithm and (iii) the incorporation of importance sampling concepts into the stochastic programming framework so as to allow the solution of large instances of the problem. Computational results demonstrate the effectiveness of the proposed methodology by solving instances significantly larger than those reported in related works.

This thesis considers the design and analysis of humanitarian supply chains, by which we mean those systems that deliver goods and services in response to natural or man-made disasters as well as ongoing public health challenges. In the first part of the thesis, we introduce a class of problems motivated by humanitarian logistics systems with decentralized decision makers. In contrast to traditional optimization problems in which a centralized planner determines the actions of all entities in the system, decentralized systems are characterized by individual decision makers who make choices to optimize their own objectives and whose actions impact the overall system performance. Decentralized systems often perform poorly in comparison to centralized ones, but centralization is costly or impractical to implement in many circumstances. The goal of this part of the thesis is to characterize the impact of decentralized decision making and identify ways to mitigate this impact. Using concepts from optimization and game theory, we model systems in which individuals choose a facility to visit to receive service, such as during a disaster response, making their choices based on travel time, congestion, and weights on congestion. These weights represent the relative importance individuals place on congestion in their objectives. We provide an efficient algorithm for finding a stable, or equilibrium, solution from which no individual can improve her own objective value by switching unilaterally. We show that the worst- and best-case performances of decentralized solutions depend on the importance individuals place on congestion. Finally, we introduce a mechanism under which the central optimal solution is also an equilibrium. The mechanism acts by influencing the importance individuals place on congestion, and we characterize the values that this importance can and must be to achieve stability. We introduce models to find values of the mechanism that optimize particular policy objectives and show that these models can be solved efficiently. The second part of the thesis describes the application of the ideas developed in the first part to data from a large-scale effort to deliver a limited supply of products to a large number of people in a short time. The goal of this part of the thesis is to understand the impact of decentralized decision making on local access to an actual product and quantify correlations between inequities in access and socioeconomic variables. We find that both the centralized and decentralized systems lead to inequity in access, but the impact is greater in decentralized systems with user choice. The differences in access are correlated with several socioeconomic variables, but these relationships vary across geographic space. This study integrates tools from optimization, game theory, spatial statistics, and geographic information systems in a novel way. The results confirm the importance of accounting for decentralized behavior in system design and point to opportunities to use the mechanism from the first part of the thesis in future distribution efforts of this nature. The study also leads to policy recommendations, namely that planners consider the impact on equity prior to implementing distribution plans and work to recruit additional service providers in areas that have exhibited inequities in the past. The third part of the thesis employs empirical methods to characterize a successful humanitarian supply chain and identify practices from which other organizations can learn to improve their operations. The hurricane response process used by Waffle House Restaurants has been recognized nationally for its effectiveness. We document the process and describe the supply chain concepts that contribute to its success. Further, we place the company's practices in the context of the literature on supply chain disruption, crisis management, and humanitarian logistics. This study provides insight for other organizations that seek to improve their resilience to supply chain disruptions, whether these are caused by natural disasters or other events. The study also led to the creation of teaching materials to help business and engineering students identify the challenges faced in humanitarian supply chains, the ways that operations research methodologies can be used to improve decisions, and the opportunities for cross-learning between humanitarian organizations and the private sector.

The occurrence of devastating natural disasters in the past several years have prompted communities, responding organizations, and governments to seek ways to improve disaster preparedness capabilities locally, regionally, nationally, and internationally. A holistic approach to design used in the aerospace and industrial engineering fields enables efficient allocation of resources through applied parametric changes within a particular design to improve performance metrics to selected standards. In this research, this methodology is applied to disaster preparedness, using a community's time to restoration after a disaster as the response metric. A review of the responses from Hurricane Katrina and the 2010 Haiti earthquake, among other prominent disasters, provides observations leading to some current capability benchmarking. A need for holistic assessment and planning exists for communities but the current response planning infrastructure lacks a standardized framework and standardized assessment metrics. Within the humanitarian logistics community, several different metrics exist, enabling quantification and measurement of a particular area's vulnerability. These metrics, combined with design and planning methodologies from related fields, such as engineering product design, military response planning, and business process redesign, provide insight and a framework from which to begin developing a methodology to enable holistic disaster response planning. The developed methodology was applied to the communities of Shelby County, TN and pre-Hurricane-Katrina Orleans Parish, LA. Available literature and reliable media sources provide information about the different values of system parameters within the decomposition of the community aspects and also about relationships among the parameters. The community was modeled as a system dynamics model and was tested in the implementation of two, five, and ten year improvement plans for Preparedness, Response, and Development capabilities, and combinations of these capabilities. For Shelby County and for Orleans Parish, the Response improvement plan reduced restoration time the most. For the combined capabilities, Shelby County experienced the greatest reduction in restoration time with the implementation of Development&Response capability improvements, and for Orleans Parish it was the Preparedness&Response capability improvements. Optimization of restoration time with community parameters was tested by using a Particle Swarm Optimization algorithm. Fifty different optimized restoration times were generated using the Particle Swarm Optimization algorithm and ranked using the Technique for Order Preference by Similarity to Ideal Solution. The optimization results indicate that the greatest reduction in restoration time for a community is achieved with a particular combination of different parameter values instead of the maximization of each parameter.