Disaster Management Cycle-Based Integrated Humanitarian Supply Network Management

While logistics research recently has placed increased focus on disruptionmanagement, few studies have examined the response and recovery phases in post-disaster operations. We present a multiple-objective, integrated network optimizationmodel for making strategic decisions in the supply distribution and network restorationphases of humanitarian logistics operations. Our model provides an equity- or fairness-based solution for constrained capacity, budget, and resource problems in post-disasterlogistics management. We then generate efficient Pareto frontiers to understand the trade-off between the objectives of interest.Next, we present a goal programming-based multiple-objective integratedresponse and recovery model. The model prescribes fairness-based compromise solutionsfor user-desired goals, given limited capacity, budget, and available resources. Anexperimental study demonstrates how different decision making strategies can beformulated to understand important dimensions of decision making.Considering multiple, conflicting objectives of the model, generating Pareto-optimal front with ample, diverse solutions quickly is important for a decision maker tomake a final decision. Thus, we adapt the well-known Non-dominated Sorting GeneticAlgorithm II (NSGA-II) by integrating an evolutionary heuristic with optimization-basedtechniques called the Hybrid NSGA-II for this NP-hard problem. A Hypervolume-basedtechnique is used to assess the algorithm’s effectiveness. The Hazards U.S. Multi-Hazard(Hazus)-generated regional case studies based on earthquake scenarios are used todemonstrate the applicability of our proposed models in post-disaster operations

An Exploratory Study of Patient Falls

Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body

Supply Chain Management and Management Science: A Successful Marriage

The last century has witnessed extant studies on the applications of Management Science (MS) to a diverse set of Supply Chain Management (SCM) issues. This paper provides an overview of the contribution of MS within SCM. A framework is developed in this paper with a sampling of MS contributions to major SCM dimensions. Future research directions are presented

Decision support framework for supply chain planning with flexible demand

The most challenging issue of today’s production management is certainly to manage networked organisations under an uncertain demand so that to provide a good service to the customer at low cost. In this article, a model of the decision making parameters involved in this management process is suggested, on the base of case studies. A mixed integer linear planning model embedded in a framework simulating a rolling horizon planning process is described on the base of this analysis. The model takes into account the capabilities of reaction of the planned system and of its environment (suppliers, subcontractors and customers), as well as the corresponding costs. The suggested simulation framework may assist the decision maker for coping with an uncertain or flexible demand, using various planning strategies. Some possible applications of this simulation framework are given in order to illustrate how it can help to solve various types of practical planning problems

Information and decentralization in inventory, supply chain, and transportation systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.Includes bibliographical references (p. 199-213).This thesis investigates the impact of lack of information and decentralization of decision-making on the performance of inventory, supply chain, and transportation systems. In the first part of the thesis, we study two extensions of a classic single-item, single-period inventory control problem: the "newsvendor problem." We first analyze the newsvendor problem when the demand distribution is only partially specified by some moments and shape parameters. We determine order quantities that are robust, in the sense that they minimize the newsvendor's maximum regret about not acting optimally, and we compute the maximum value of additional information. The minimax regret approach is scalable to solve large practical problems, such as those arising in network revenue management, since it combines an efficient solution procedure with very modest data requirements. We then analyze the newsvendor problem when the inventory decision-making is decentralized. In supply chains, inventory decisions often result from complex negotiations among supply partners and might therefore lead to a loss of efficiency (in terms of profit loss).(cont.) We quantify the loss of efficiency of decentralized supply chains that use price-only contracts under the following configurations: series, assembly, competitive procurement, and competitive distribution. In the second part of the thesis, we characterize the dynamic nature of traffic equilibria in a transportation network. Using the theory of kinematic waves, we derive an analytical model for traffic delays capturing the first-order traffic dynamics and the impact of shock waves. We then incorporate the travel-time model within a dynamic user equilibrium setting and illustrate how the model applies to solve a large network assignment problem.by Guillaume Roels.Ph.D

Strategic Inventory and Supply Chain Behavior

Based on a serial supply chain model with 2-periods and price-sensitive demand, we present the first experimental test of the effect of strategic inventories on supply chain performance. In theory, if holding costs are low enough, the buyer builds up a strategic inventory (even if no operational reasons for stock-holding exist) to limit the supplier\u27s market power, to increase the own profit share, and to enhance the overall supply chain performance. The supplier anticipates the effect of the strategic inventory and differentiates prices to capture a part of the increased supply chain profits. Our results show that the positive effects of strategic inventories are even more pronounced than theoretically predicted, because strategic inventories empower buyers to reduce payoff inequalities and suppliers exhibit a willingness to reduce inequalities as long as their payoff remains above a certain threshold. Overall, strategic inventories have a double positive effect, a strategic and a behavioral, both reducing the average wholesale prices and damping the double marginalization effect and the latter leading to more equitable payoffs

Strategic network planning in biomass-based supply chains

Fossil resources are limited and will run short. Moreover, the extensive usage of fossil resources is discussed as a key driver for climate change which means that a changeover in basic economic and ecological thinking is necessary. Especially for energy production, there has to be a movement away from the usage of fossil resources and towards renewable resources like wind, water, sun, or biomass. Within the first part of this work a structured review of recent literature on the long-term, strategic planning of biomass-based supply chains is provided. Therefore, in the first step, the overall research field bioeconomy by means of the various utilization pathways of biomass is structured and the demand-oriented view of supply chain management models and the supply-oriented view of bioeconomy are combined. In the second step, a literature review of operations research models and methods for strategic supply chain planning in biomass-based industries are provided. Thirdly, trends are identified and conclusions about research gaps are drawn. One of the identified research gaps is to make biomass-based supply chains profitable on their own, i.e., without governmental subsidies. Therefore, new optimization models are necessary, which should be as close to reality as possible, by for example considering risks and actual surrounding constraints concerning the legal framework. Within the second part of this work, an approach for strategic optimization of biogas plants considering increased flexibility is developed. Biogas plants can produce their energy flexibly and on-demand if their design is adjusted adequately. In order to achieve a flexibly schedulable biogas plant, the design of this plant has to be adapted to decouple the biogas and electricity production. Therefore, biogas storage possibilities and additional electrical capacity are necessary. The investment decision about the size of the biogas storage and the additional electrical capacity depends on the fluctuation of energy market prices and the availability of governmental subsidies. This work presents an approach supporting investment decisions to increase the flexibility of a biogas plant by installing gas storages and additional electrical capacities under consideration of revenues out of direct marketing at the day-ahead market. In order to support the strategic, long-term investment decisions, an operative plant schedule for the future, considering different plant designs given as investment strategies, using a mixed-integer linear programming (MILP) model in an uncertain environment is optimized. The different designs can be evaluated by calculating the net present value (NPV). Moreover, an analysis concerning current dynamics and uncertainties within spot market prices is executed. Furthermore, the influences concerning the variation of spot market prices compared to the influence of governmental subsidies, in particular, the flexibility premium, are revealed by computational results. Besides, the robustness of the determined solution is analyzed concerning uncertainties. The focus of the third part of the work is to consider variable substrate feeding in the mentioned optimization approach because it is expected that variable substrate feeding and thus a demand-oriented biogas production can influence the optimized plant design. In order to support this extension, an operative plant schedule for the future, considering (non-) linear technical characteristics of the biogas plant and the legal framework is optimized. Therefore, mixed-integer linear programming models with integrated approximation approaches of non-linear parts, representing the biogas production rates, are constructed. Furthermore, the influences of fluctuating spot market prices, governmental subsidies, and biomass feedstock prices on the decisions are analyzed for a fictional case example, which is based on a biogas plant in southern Germany. These numerical experiments show that variable substrate feeding can play a decisive role during the optimization of a biogas plant schedule as part of a long-term design optimization. However, the size of the strategic optimization problem makes the use of a heuristic solution algorithm necessary.Fossile Ressourcen sind begrenzt und werden zur Neige gehen. Darüber hinaus wird über die extensive Nutzung fossiler Ressourcen als wesentlicher Treiber des Klimawandels diskutiert, so dass ein Umdenken in der ökonomischen und ökologischen Grundhaltung notwendig ist. Insbesondere bei der Energieerzeugung muss eine Abkehr von der Nutzung fossiler Ressourcen und eine Ausrichtung auf erneuerbare Ressourcen wie Wind, Wasser, Sonne oder Biomasse erfolgen. Im ersten Teil dieser Arbeit wird ein strukturierter Überblick über die aktuelle Fachliteratur zur langfristigen, strategischen Planung von biomassebasierten Supply Chains gegeben. Dazu wird in einem ersten Schritt das gesamte Forschungsfeld "Bioökonomie" anhand der verschiedenen Nutzungspfade von Biomasse strukturiert und die nachfrageorientierte Sichtweise von Supply Chain Management Modellen und die angebotsorientierte Sichtweise der Bioökonomie zusammengeführt. Im zweiten Schritt wird ein Literaturüberblick über Operations-Research-Modelle und Methoden zur strategischen Supply-Chain-Planung in biomassebasierten Branchen gegeben. Im dritten Schritt werden Trends identifiziert und Schlussfolgerungen über Forschungslücken gezogen. Eine der identifizierten Forschungslücken besteht darin, biomassebasierte Supply Chains selbständig, d.h. ohne staatliche Subventionen, profitabel zu machen. Hierfür sind neue Optimierungsmodelle notwendig, die möglichst realitätsnah sein sollten, indem sie z.B. Risiken und tatsächliche Rahmenbedingungen bezüglich der rechtlichen Vorgaben berücksichtigen. Im zweiten Teil dieser Arbeit wird ein Ansatz zur strategischen Optimierung von Biogasanlagen unter Berücksichtigung einer Flexibilitätserhöhung entwickelt. Biogasanlagen können bei geeigneter Auslegung ihre Energie flexibel und bedarfsgerecht produzieren. Um eine Biogasanlage flexibel planbar zu betreiben, muss das Design dieser Anlage so angepasst werden, dass die Biogas- und Stromproduktion entkoppelt werden. Dazu sind Biogasspeichermöglichkeiten und zusätzliche elektrische Kapazität notwendig. Die Investitionsentscheidung über die Größe des Biogasspeichers und der zusätzlichen elektrischen Kapazität hängt von der Schwankung der Energiemarktpreise und der Verfügbarkeit staatlicher Fördermittel ab. Diese Arbeit stellt einen Ansatz zur Unterstützung von Investitionsentscheidungen zur Erhöhung der Flexibilität einer Biogasanlage durch die Installation von Gasspeichern und zusätzlichen elektrischen Kapazitäten unter Berücksichtigung von Erlösen aus der Direktvermarktung am Day-Ahead-Markt vor. Um die strategischen, langfristigen Investitionsentscheidungen zu unterstützen, wird ein operativer Anlagenfahrplan für die Zukunft unter Berücksichtigung verschiedener Anlagendesigns, die als Investitionsstrategien vorgegeben sind, mit Hilfe eines gemischt-ganzzahligen linearen Optimierungsmodells (MILP), unter Berücksichtigung von Unsicherheit, optimiert. Die verschiedenen Designs können durch die Berechnung des Kapitalwerts (NPV) bewertet werden. Darüber hinaus wird eine Analyse der aktuellen Dynamik und der Unsicherheiten der Spotmarktpreise durchgeführt. Darüber hinaus werden die Einflüsse der Varianz der Spotmarktpreise im Vergleich zum Einfluss staatlicher Subventionen, insbesondere der Flexibilitätsprämie, durch Berechnungsergebnisse aufgezeigt. Außerdem wird die Robustheit der ermittelten Lösung hinsichtlich der Unsicherheiten analysiert. Der Fokus des dritten Teils der Arbeit liegt auf der Berücksichtigung eines variablen Substratmanagements in dem entwickelten Optimierungsansatz, da erwartet wird, dass eine variable Substrateinspeisung und damit eine bedarfsgerechte Biogasproduktion das optimierte Anlagendesign beeinflussen kann. Um diese Erweiterung umzusetzen, wird ein operativer Anlagenfahrplan für die Zukunft unter Berücksichtigung (nicht-) linearer technischer Eigenschaften der Biogasanlage und der gesetzlichen Rahmenbedingungen optimiert. Dazu werden gemischt-ganzzahlige lineare Optimierungsmodelle mit integrierten Approximationsansätzen der nichtlinearen Anteile, welche die Biogasproduktionsraten repräsentieren, konstruiert. Des Weiteren werden die Einflüsse von schwankenden Spotmarktpreisen, staatlichen Förderungen und Biomasse-Rohstoffpreisen auf die Entscheidungen für ein fiktives Fallbeispiel, das auf einer Biogasanlage aus Süddeutschland basiert, analysiert. Die numerischen Experimente zeigen, dass die variable Substrateinspeisung bei der Optimierung des Fahrplans einer Biogasanlage im Rahmen einer langfristigen Anlagenoptimierung eine entscheidende Rolle spielen kann. Die Größe des strategischen Optimierungsproblems macht jedoch den Einsatz eines heuristischen Lösungsalgorithmus notwendig

Comparative analysis on decision making in the case of nuclear power plant development in the Republic of Kazakhstan

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2019. 2. Heo, Eunnyeong.카자흐스탄은 우라늄 최대생산국이자 수출국이면서 동시에 구 소련연방국가이기에 원자력산업의 개발에 대한 관심이 크다. 풍부한 우라늄 매장량은 특히 카자흐스탄 정부가 원자력발전에 대한 정책을 지속적으로 논의하여온 대표적인 이유이다. 그러나 원자력발전이 실제로 카자흐스탄에서 개시되기 위해는 많은 제약과 한계를 넘어야 한다. 본 논문은 이러한 배경을 바탕으로 하여, 카자흐스탄에서 원자력 발전을 시작하기 위한 전제조건들이 무엇인지 찾고 또한 찾은 조건들의 중요도를 비교 분석하였다. 분석방법론으로는 복잡한 의사결정구조를 평가하는 분석에 활발히 사용되고 있는 Analytic Hierarchy Process (AHP)를 사용하였다. 본 연구에서는 먼저 관련 문헌을 분석하여 전제조건들을 나열하고, 이들을 전문가설문을 통하여 4개의 중분류 조건과 12개의 세부조건으로 정리하였다. 다음으로, 카자흐스탄 정부 중 실무를 담당하는 에너지부와 재정을 담당하는 투자개발부 소속 공무원들을 대상으로 하여 4개 중분류 조건 및 12개 세부조건들을 대상으로 AHP 분석을 실시하여 이들간의 중요도를 비교 분석하였다. 분석결과, 투자개발부 공무원들은 4개 중분류 중 경제성이 가증 중요도가 높다고 판단한 반면, 에너지부 공무원들은 환경성이 가장 중요하다고 판단하고 있음을 확인할 수 있었다. 두 부처 공무원들 모두 사회정치적 조건들은 중요하지 않다고 판단하였다. 세부 기준 중에는 건설비용과 회수기간 등이 투자개발부 공무원들이 가장 중요하게 생각한 조건인 반면 에너지부 공무원들은 소음과 주민수용성을 들었다. 한편 연구개발이나 효율성 등은 중요도가 낮게 나와 카자흐스탄 정부의 원자력에 대한 태도를 확인할 수 있었다. 주요어 : Analytic Hierarchy Process (AHP), 카자흐스탄, 원자력발전, 정부정책. 학 번 : 2017-29469Despite that almost all former USSR republics refused Soviet nuclear weapons, only Kazakhstan could reap the maximum of reputational benefits from this and make the nuclear-free status a part of its international reputation. Being among largest producers and exporters of uranium in the world, Kazakhstan is directly interested in the development of the nuclear industry. The abundance of uranium resources and the provision of continuous supplies of low-enriched uranium provides an additional incentive for the development of domestic nuclear programs. As a result, the issue of necessity of a nuclear power plant in Kazakhstan is occasionally discussed in the government. In this regard, there are many questions that have to be answered before the construction of the nuclear power plant could begin. This research tries to investigate and rank the assessment criteria and factors that should be taken into account for the construction of a nuclear power plant in Kazakhstan. The methodology of this study consists of two steps: First, a detailed literature review is conducted in order to identify the assessment criteria and sub-criteria for government officials in decision making. The second step covers obtaining opinions from the experts in energy-related area. The collected information is analyzed using Analytic Hierarchy Process (AHP). With the help of the AHP, the weight of each criterion and sub-criterion is calculated. The results show that among all four criteria, the Economic criterion is the most crucial for decision makers from the Ministry for Investments and Development. On the other hand, the Environmental criterion is the most important among decision makers from the Ministry of Energy. The Environmental criterion was assessed by the Ministry for Investments and Development as the least important factor in the construction of a nuclear power plant. Interestingly, both decision making groups did not assess the Socio-Political criterion as an important barrier. Moreover, government officials from the Ministry for Investment and Development believe that Construction cost and Payback period are the most important barriers in the development of a nuclear power plant, however, Social Acceptance and Noise play only an insignificant role in the decision making. In the case of the Ministry of Energy, criteria such as Impact on environment and Land use are the most significant, while Efficiency and R&D were assessed with a low importance. Key words: Analytic Hierarchy Process (AHP), Republic of Kazakhstan, Criteria, Decision making, Nuclear energy, Nuclear power plant. Student number: 2017-29469Abstract iii Contents v List of Tables vii List of Figures viii Chapter 1. Introduction 1 1.1 Overall introduction 1 1.2 Development of energy sector in Kazakhstan 3 1.3 Energy sector in the Republic of Kazakhstan 9 1.4 Purpose of study 16 1.5 Research motivation 21 1.6 Research questions and thesis structure 23 Chapter 2. Literature review and methodology for comparative analysis 25 2.1 Literature review 25 2.2 The Analytic Hierarchy Process 31 2.3 Why the Analytic Hierarchy Process? 34 2.4 Main steps of the AHP 37 2.4.1 Representing the initial problem in the form of a hierarchical structure 37 2.4.2 Pairwise comparison of individual hierarchy component 38 2.4.3 Obtaining normalized matrix 40 2.4.4 Consistency index and consistency ratio 41 Chapter 3. Model and Data 43 3.1 Previous studies 43 3.2 Basic concept of barriers related to the construction of nuclear power plants 50 3.3 Description of criteria 52 3.3.1 Socio-Political criterion 52 3.3.2 Technical criterion 53 3.3.3 Economic criterion 54 3.3.4 Environmental criterion 55 3.4 Consistency test 58 Chapter 4. Results of AHP 65 4.1 Weights of main criteria 65 4.2 Weights of sub criteria within Socio-Political criterion 68 4.3 Weights of sub criteria within Technical criterion 71 4.4 Weights of sub criteria within Economic criterion 73 4.5 Weights of sub criteria within Environmental criterion 75 4.6 Results of Global Priorities 77 4.7 Comparative analysis 81 4.7.1 Ministry for Investments and Development 81 4.7.2 Ministry of Energy 83 4.7.3 Weight of each barrier and analysis of differences between two decision making groups ………..85 Chapter 5. Conclusion 87 5.1 Overall conclusion 88 5.2 Limitations of Study 90 Bibliography 91 Appendix 1: Questionaire 103 Abstract (Korean) 113 Aknowledgement 115Maste

Decision support system for a reactive management of disaster-caused supply chain disturbances

This research contribution presents the Reactive Disaster and supply chain Risk decision Support System ReDRiSS which supports decision-makers of logistical disaster management in the immediate aftermath of a supply chain disturbance. ReDRiSS suggests a methodology which combines approaches from scenario techniques, operations research and decision theory. Two case studies are provided which focus on decision situations of humanitarian logistics and of business continuity management