Disaster management and its economic implications

Das Ziel dieser Arbeit ist es, aktuelle Forschungsschwerpunkte im Bereich des Katastrophenmanagements in der Operational Research Literatur aufzuzeigen. Katastrophenmanagement umfasst in diesem Zusammenhang einerseits Naturkatastrophen wie geophysikalische und hydro-meteorologische Katastrophen, technologische Katastrophen wie industrielle Unfälle, Transportunfälle und sonstige Unfälle, und andererseits die verschiedenen Formen des Terrorismus, allgemeinen Terrorismus sowie Bioterrorismus. Da die Anzahl und das Ausmaß von Katastrophen immer weiter zunehmen ist auch eine immer größere Notwendigkeit für die Entwicklung, den Einsatz und die wirtschaftliche Beurteilung der jeweiligen Strategien gegeben. Der erste Teil dieser Arbeit gibt einen Überblick über die Literatur im Bereich des Katastrophenmanagements und umfasst Simulation, Katastrophenmanagement in Krankenhäusern und die Rolle von Versicherungen im Katastrophenmanagementprozess. Im zweiten Teil wird eine Taxonomie entwickelt, deren Kategorien auf den Modellen und Ergebnissen der Literatur beruhen. Einerseits werden allgemeine Modelleigenschaften wie die Ebene im Katastrophenmanagementprozess, der Modelltyp und die Anwendungsgebiete der Modelle untersucht. Andererseits stellen die Art der Intervention und die Anwendbarkeit für die unterschiedlichen Katastrophenklassen weitere Kategorien der Taxonomie dar. Es wurden 90 Artikel, die beispielhaft für die Forschungsrichtungen im Bereich des Katastrophenmanagements der letzten 25 Jahre stehen, ausgewählt, und entsprechend den jeweiligen Kategorien der Taxonomie zugeordnet. Das Hauptaugenmerk der Taxonomie liegt auf der wirtschaftlichen Analyse, die wirksamkeitsbezogene, ressourcenbezogene und kostenbezogene Parameter umfasst. Es wird gezeigt ob und welche wirtschaftliche Analyse wie beispielsweise die Kosten-Nutzwert- Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse angewendet wird um die in den Artikeln beschriebenen Interventionen zu evaluieren. Es wird gezeigt, dass erhebliche Verbesserungen für die verschiedenen Katastrophentypen und in den verschiedenen Situationen erzielt werden können. Eingeschränkte Datenverfügbarkeit schränkt in vielen Fällen die Einsetzbarkeit der Modelle in realen Situationen ein. Im Allgemeinen ist erkennbar, dass Kooperation und Koordination zwischen den beteiligten Einheiten ausschlaggebend für den zeitgerechten und effizienten Einsatz der knappen Ressourcen sind. Oftmals erzielt der gemeinsame Einsatz mehrerer Maßnahme ein deutlich besseres Ergebnis als der Einsatz von lediglich einem einzigen Instrument. Die Taxonomie unterstreicht dass trotz der großen Fülle an Literatur im Bereich des Katastrophenmanagements nur wenige Autoren auf die Kosten-Nutzwert-Analyse, die Kosten-Wirksamkeits-Analyse und die Kosten-Nutzen-Analyse als Hilfsmittel zur wirtschaftlichen Analyse zurückgreifen. In Zukunft, um Interventionen erfolgreich evaluieren zu können oder die beste aus mehreren Interventionen bestimmen zu können wird es immer wichtiger werden, diese Art von wirtschaftlichen Analysen anzuwenden.This thesis intends to demonstrate current research directions in the field of disaster management in the Operational Research literature. Disaster management in this context comprises the management of natural, such as geophysical and hydro-meteorological, and technological disasters, such as industrial accidents, transportation accidents, and miscellaneous accidents, as well as the management of the different terrorism forms, general terrorism and bioterrorism. As the occurrence of disasters is getting more and more frequent and the accumulated loss of these events is getting higher and higher, there is a strong need for the development, implication and economic evaluation of strategies to counter these disasters. In the first part of the thesis, a general overview of the literature is given, including a focus on simulation, disaster management in hospitals, and the role of insurances in the disaster management process. The second part encompasses the taxonomy which focuses on models and outcomes presented in the literature. As a result of the review of the literature, appropriate categories for the disaster management taxonomy are derived. On the one hand, an overview of general model features, i.e., the level of disaster management, model type and methods of application is given. On the other hand, the type of intervention used and the practicability for different disaster types are discussed. 90 papers, illustrative main examples of the research directions of the last 25 years, were selected for deeper investigation and classified according to the main criteria analyzed in the articles. The main focus of the taxonomy lies on the economic analysis, which encompasses effectiveness-related, resource-related, and cost-related parameters and shows the type of economic analysis used in the literature. We analyze whether economic analysis, i.e., costutility, cost-effectiveness, and cost-benefit are used to investigate different interventions and what type of analysis has been chosen by the authors. Policy implications and results show that considerable improvements can be achieved for different disastrous events and in different situations. Limited data availability constrains the outcomes of the models and their applicability to real-world situations. In general, cooperation and coordination of the entities involved are crucial to guarantee timely and efficient assignment of scarce resources. Furthermore, different authors confirm that a combination of various measures often achieves a better outcome than if tools are used autonomously. The taxonomy has underlined that although there exists a vast disaster management literature dealing with various problems related to mitigation, preparedness, response and recovery from disasters, there are only a few authors evaluating the actions taken through economic analyses such cost-utility, cost-effectiveness, or cost-benefit analysis. In the future, to be able to evaluate interventions, or to figure out the most effective intervention among several interventions, it is crucial to stronger rely on the abovementioned economic analyses

Real-time Decision Making on Helicopter Dispatch during Multiple Forest Fires

On average there are over 500 forest fires burning more than 3,700 ha each year in South Korea. Between 2014 and 2018, 62 percent of forest fires were multiple fires burning simultaneously in more than two different locations across the country. These multiple fires make it difficult to make decisions of resource dispatch for suppression, as they compete for limited resources, such as helicopters. In order to support and improve decision-making in real-time helicopter dispatch, we developed a conceptual decision framework that lays out the process of information gathering, prioritization, and problem-solving. We developed an integer linear programming (ILP) model to solve helicopter dispatch problems. The model uses real-time data on available helicopter resources and fire spread to develop dispatch decisions while minimizing both suppression costs and burn perimeters. We developed five hypothetical forest fire events and applied the model to demonstrate the utility of the optimization model. We compared the model solutions with the manual solutions obtained from the Korea Forest Service for model validation. Our results show that the optimization model can rapidly analyze various fire suppression scenarios and provide a wide range of helicopter dispatch solution options. This can be useful to decision-makers as it can provide insights about decision sensitivity and bounds. The decision model can provide an analytical tool to assist decision-makers in determining suppression objectives, prioritizing resource allocations, and developing effective and efficient fire suppression solutions

A stochastic mixed integer programming approach to wildfire management systems

Wildfires have become more destructive and are seriously threatening societies and our ecosystems throughout the world. Once a wildfire escapes from its initial suppression attack, it can easily develop into a destructive huge fire that can result in significant loss of lives and resources. Some human-caused wildfires may be prevented; however, most nature-caused wildfires cannot. Consequently, wildfire suppression and contain- ment becomes fundamentally important; but suppressing and containing wildfires is costly. Since the budget and resources for wildfire management are constrained in reality, it is imperative to make important decisions such that the total cost and damage associated with the wildfire is minimized while wildfire containment effectiveness is maximized. To achieve this objective, wildfire attack-bases should be optimally located such that any wildfire is suppressed within the effective attack range from some bases. In addition, the optimal fire-fighting resources should be deployed to the wildfire location such that it is efficiently suppressed from an economic perspective. The two main uncertain/stochastic factors in wildfire management problems are fire occurrence frequency and fire growth characteristics. In this thesis two models for wildfire management planning are proposed. The first model is a strategic model for the optimal location of wildfire-attack bases under uncertainty in fire occurrence. The second model is a tactical model for the optimal deployment of fire-fighting resources under uncertainty in fire growth. A stochastic mixed-integer programming approach is proposed in order to take into account the uncertainty in the problem data and to allow for robust wildfire management decisions under uncertainty. For computational results, the tactical decision model is numerically experimented by two different approaches to provide the more efficient method for solving the model

Dispositivo aéreo de combate a incêndios florestais : proposta de um modelo para minimização de custos

Mestrado em Contabilidade, Fiscalidade e Finanças EmpresariaisO Sistema Nacional de Defesa da Floresta Contra Incêndios tem sido desenvolvido e aprimorado nos últimos anos, devido à contínua ameaça dos incêndios à floresta portuguesa. Neste sistema, a vertente do combate a incêndios é a que mais alterações tem sofrido e onde mais se tem investido. A Autoridade Nacional de Proteção Civil (ANPC) contrata meios aéreos (helicópteros e aviões) como parte integrante da sua estratégia de combate a incêndios. Em oposição a uma frota própria, a ANPC, tem recorrido, cada vez mais, a meios contratados. Apesar de ser verificada uma crescente dependência de meios contratados, não existem estudos que determinem qual o número ideal de meios a contratar ou a comprar. O presente estudo utiliza a abordagem de construção de modelos de investigação operacional, disponível, por exemplo, em Hillier & Lieberman (2010), para desenvolver um modelo conceptual de decisão, de modo a auxiliar o processo de tomada de decisão, ou seja, a escolha entre o número e o tipo de meios, próprios ou a contratar. A otimização definida visa a ajuda na tomada de decisão apontando para aquela que permita minimizar os custos do dispositivo aéreo de combate a incêndios. Com este trabalho procura-se contribuir para um melhor planeamento orçamental da ANPC e, consequentemente, para uma minimização de custos associados ao combate a incêndios florestais.The National Forest Fire Protection System has been developed and improved in recent years, due to the continuous threat of fires to the Portuguese forest. In this system, the aspect of wildfire suppression is the one that has suffered the most changes and where more has been invested. The Autoridade Nacional de Proteção Civil (ANPC) hire aerial forces services (helicopter and aircraft) as part of its wildfire suppression strategy. ANPC is increasingly relying on contract aerial fleet as opposed to own one. Despite this increasing reliance on contractors, there have been no studies to determine what the optimal mix should be. This study uses the operational research modeling approach of Hillier & Lieberman (2010) to develop a conceptual decision model to assist the decision-making process and to choose between the number and type of means to own and to hire. The optimization defined aims at aiding decision-making towards the one that allows to minimize the costs of the aerial fire-fighting program. The aim of this work is to contribute to a better budget planning of the ANPC and consequently to a cost reduction in forest firefighting.info:eu-repo/semantics/publishedVersio

Forest fire management in Portugal : developing system insights through models of social and physical dynamics

Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 122-135).Managing forest fires is a serious national problem in Portugal. Burned area has increased steadily over the past several decades, with particularly devastating years in 2003 and 2005. Ignitions also spike dramatically in summer, which greatly strains firefighting resources and leads to fires that are insufficiently extinguished and later may rekindle. The response of policymakers and fire managers to these problems has largely been to increase fire suppression capacity and technology deployment. This research asks, what are the side effects or unintended consequences of policies dedicated to large and aggressive suppression forces? Much of the previous work in forest fire management focuses on narrowly-defined, static problems solved using optimization analysis. This research uses dynamic analysis, specifically System Dynamics, to explore how self-regulating feedback loops affect the outcomes of forest fire management decisions over time. Two models are developed. The strategic model explores the dynamic between suppression and prevention expenditure and its effect on long-term burned area. The operational model explores the dynamics through which rekindled fires occur. The results from both models show that interactions between relevant social and physical systems, in the form of public or institutional pressure, can force aggressive suppression decisions into practice. Furthermore, strict adherence to these policies can trap each system in a state of long-run worse behavior due to the overwhelming effects of negative feedback loops. Policy recommendations based on the results, and informed by an in-depth analysis of relevant stakeholders and impediments to implementation, are also presented.by Ross D. Collins.S.M.in Technology and Polic

Irreducible Infeasible Subsystem Decomposition for Probabilistically Constrained Stochastic Integer Programs

This dissertation explores methods for finding irreducible infeasible subsystems (IISs) of systems of inequalities with binary decision variables and for solving probabilistically constrained stochastic integer programs (SIP-C). Finding IISs for binary systems is useful in decomposition methods for SIP-C. SIP-C has many important applications including modeling of strategic decision-making problems in wildfire initial response planning. New theoretical results and two new algorithms to find IISs for systems of inequalities with binary variables are developed. The first algorithm uses the new theory and the method of the alternative polyhedron within a branch-and-bound (BAB) approach. The second algorithm applies the new theory and the method of the alternative polyhedron to a system in which zero/one box constraints are appended. Decomposition schemes using IISs for binary systems can be used to solve SIP-C. SIP-C is challenging to solve due to the generally non-convex feasible region. In addition, very weak lower (upper) bounds on the objective function are obtained from the linear programming (LP) relaxation of the deterministic equivalent problem (DEP) to SIP-C. This work develops a branch-and-cut (BAC) method based on IIS inequalities to solve SIP-C with random technology matrix and random righthand- side vector. Computational results show that the LP relaxation of the DEP to SIP-C can be strengthened by the IIS inequalities. SIP-C modeling can be applied to wildfire initial response planning. A new methodology for wildfire initial response that includes a fire behavior simulation model, a wildfire risk model, and SIP-C is developed and tested. The new method- ology assumes a known standard response needed to contain a fire of given size. Likewise, this methodology is used to evaluate deployment decisions in terms of the number of firefighting resources positioned at each base, the expected number of escaped and contained fires, as well as the wildfire risk associated with fires not receiving a standard response. A study based on the Texas district 12 (TX12) that is one of the Texas A&M Forest Service (TFS) fire planning units in east Texas demonstrates the effectiveness of the new methodology towards making strategic deployment decisions for wildfire initial response planning

Empirical Analysis of Firefighting – Large-Fire Suppression in Victoria, Australia

Large fires can cause the deaths of hundreds of people, burn thousands of homes, and cost billions of dollars in damages. Suppression is the primary means of large-fire management. Most suppression costs, billions of dollars, come from large-fire suppression. Yet, formal knowledge of large-fire suppression is limited. Fire managers make decisions that impact the lives of thousands of people. As the effectiveness of large-fire suppression is mainly unquantified, there is little beyond their tacit knowledge to guide decisions. Before we address effectiveness, we must address a fundamental question: ‘How are suppression resources used on large fires?’ This thesis uses qualitative and quantitative methods to answer that question. This thesis examines the suppression of 74 large fires that occurred between 2010 and 2015 in Victoria, Australia. The Department of Environment, Land, Water and Planning made this research possible by providing operational data. The first step to resolving suppression resource use was to develop a framework of large-fire suppression (Chapter 3). A qualitative document analysis was performed on a subset of ten large fires. Three approaches were involved: 1) daily fire reconstructions were completed, covering 156 days, 2) a five-stage classification of suppression was developed by analysing the reconstructions and comments in 674 operational documents, and 3) content analysis was performed on the comments to classify discrete suppression tasks. Large-fire suppression was framed as a progression through five discrete stages with 20 identified tasks. A striking result was that 57% of resource use was on tasks that fall outside of current suppression modelling and productivity research