Supply Chain Management (SCM) is a critically significant strategy that enterprises depend on to meet challenges that they face because of highly competitive and dynamic business environments of today. Supply chain management involves the entire network of processes from procurement of raw materials/services/technologies to manufacturing or servicing intermediate products/services to converting them into final products or services and then distributing and retailing them till they reach final customers. A supply chain network by nature is a large and complex, engineering and management system. Oscillations occurring in a supply chain because of internal and/or external influences and measures to be taken to mitigate/minimize those oscillations are a core concern in managing the supply chain and driving an organization towards a competitive advantage. The objective of this thesis is to develop a methodology to minimize the oscillations occurring in a supply chain by making use of the techniques of System Dynamics (SD) and Genetic Algorithms (GAs). System dynamics is a very efficient tool to model large and complex systems in order to understand their complex, non-linear dynamic behavior. GAs are stochastic search algorithms, based on the mechanics of natural selection and natural genetics, used to search complex and non-linear search spaces where traditional techniques may be unsuitable.

Manufacturing supply chains are invariably dynamic and complicated in nature. Hence, steady state models are not sufficient for analyzing and designing supply chains. Models of supply chains must accurately capture their dynamic behavior, which is determined by the structure of the organization, and the policies adopted by management. System dynamics modeling provides a powerful framework for this purpose. The use of system dynamics models in supply chain management has thus far been limited to explaining phenomenon like the bullwhip effect, and for policy development. We provide a structured approach for policy design, which doesn't rely on any simulation experiments. Further, we study the impact that information network design has on the response of supply chains. We use a combinatorial approach to develop guidelines for information network design. Further, we examine the possibility of utilizing a PID information feedback structure to enhance the responsiveness of the supply chain. Lastly, we propose a combined feedback feed-forward information structure to enable a supply chain to rapidly respond to disturbances whose effects are known. The goal of this dissertation is to provide a structured approach for the design of information network structure, and operating policy. / Ph. D.

This thesis describes and discusses the application of System Dynamics methodology as a basis for formulating diversification strategy and control policies of the largest diversifying cement company in the 'United Kingdom. The problems of the industry such as stagnant growth, cyclic and seasonal variations in cement demand, and overcapacity are described. The formulation of a SD model of the situation which captures these problems together with its equations system are presented. The model also simulates the planning and control processes for the selection, initiation and completion of both expansion and diversification investment projects. It is argued and demonstrated that the fact that these processes consist of feedback loops should and could be utilized for understanding these processes, advancing complementary theoretical concepts, and designing and formulating more 'effective systems and decision rules. An intensive analysis of the model in SD frameworks further supports these arguments. These analyses reveal the nature of the system's dynamic properties and its likely developments, the dynamic and situational nature of diversification effectiveness, and the importance of several diversification decision factors. These analyses also show how complex the formulation of a thorough and effective diversification strategy may become together with the ways and means of dealing with these complexities.. It is concluded that the thrust of an effective diversification lies with the broadening of the conventional theoretical concepts and analysis to include the dynamic characteristics of the system. It is also concluded and shown that System Dynamics methodology can provide a strong analytical basis for achieving these ends.

INTRODUCTION: Relocating hospital resources can change the efficiency of their use. The focus of this thesis is on non-emergency healthcare, specifically the relocation of staff and facilities. Relocation can be both time-consuming and costly. Predicting the expected outcome of a relocation is therefore important to determine whether the relocation is expected to have a positive or negative result. This prediction is done using a simulation model consisting of the relevant factors for hospitals. OBJECTIVES: The overall objective of this thesis is to develop a simulation model that can be used by hospital decision-makers to give them better insight into the potential outcomes of the relocation of resources. However, the most suitable model for the task first needs to be determined. Then the structure and accuracy of the model must be validated. METHODS: The thesis follows a design science methodology to aid in the development of the simulation model. With the chosen design science methodology the problem is identified; the objectives to solve it are defined; an artifact is designed, demonstrated, and evaluated; and finally, the results are communicated. RESULTS: The developed System Dynamics model can be used to assess the impact of non emergency hospital resource relocation. The user can change parameter values and get a real-time response of the expected effects the changes have on the outcome of the relocation. The model consists of four components: quality of care, staff satisfaction, patient satisfaction, and cost. These handle everything from the staff’s adaption to their new workplace, training of new staff, calculating the flow of patients in the hospital, etc. A fictive scenario based on real-world historical data isused to illustrate the use of the model and how to interpret its result. CONCLUSION: Through comparison of different simulation paradigms it is concluded that System Dynamics is the most suitable for non-emergency hospital resource relocation of staff and facilities. The developed System Dynamics model is a tool healthcare decision-makers can use to estimate the effects of their plans to relocate hospital resources. The developed model is flexible in its weight of the impacts certain parameters shall have, which makes it easier to adapt to the needs of the user. It also gives the user a responsibility to make sure that their use of the model is correct for their case. FUTURE WORK: Future work could include studying how the developed model could affect decisions in real healthcare systems. The model could also be extended to include more parameters, to manage to capture more complex behaviors.

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The National Aeronautics and Space Administration (NASA) is leading a research effort to develop a Small Aircraft Transportation System (SATS) that will expand air transportation capabilities to hundreds of underutilized airports in the United States. Most of the research effort addresses the technological development of the small aircraft as well as the systems to manage airspace usage and surface activities at airports. The Federal Aviation Administration (FAA) will also play a major role in the successful implementation of SATS, however, the administration is reluctant to embrace the unproven concept. The purpose of the research presented in this dissertation is to determine if the FAA can pursue a resource management strategy that will support the current radar-based Air Traffic Control (ATC) system as well as a Global Positioning Satellite (GPS)-based ATC system required by the SATS. The research centered around the use of the System Dynamics modeling methodology to determine the future behavior of the principle components of the ATC system over time. The research included a model of the ATC system consisting of people, facilities, equipment, airports, aircraft, the FAA budget, and the Airport and Airways Trust Fund. The model generated system performance behavior used to evaluate three scenarios. The first scenario depicted the base case behavior of the system if the FAA continued its current resource management practices. The second scenario depicted the behavior of the system if the FAA emphasized development of GPS-based ATC systems. The third scenario depicted a combined resource management strategy that supplemented radar systems with GPS systems. The findings of the research were that the FAA must pursue a resource management strategy that primarily funds a radar-based ATC system and directs lesser funding toward a GPS-based supplemental ATC system. The most significant contribution of this research was the insight and understanding gained of how several resource management strategies and the presence of SATS aircraft may impact the future US Air Traffic Control system. / Ph. D.

The lack of a consistent, rigorous testing methodology has contributed to system dynamics often not being well received in traditional modeling application areas or within the broader research community. With a foundation in taxonomy classification techniques, this research developed a modeling process risk-based framework focused on the objectives of the system dynamics methodology. This approach assists modelers in prioritizing the modeling process risk management requirements — and resources — for a project by employing a modeling process risk dictionary, a modeling process risk management methods database, and an algorithm for selecting methods based on a modeling process risk assessment. System dynamics benefits from the modeling process risk management approach include more efficient use of risk management resources and more effective management of modeling process risks. In addition, the approach includes qualities that support the achievement of verification, validation, and accreditation (VV&A) principles. A system dynamics model was developed as the apparatus for assessing the impacts of various modeling process risk management policies, including those found in the traditional system dynamics method, the more commonly practiced method, and the method as modified by the integration of the modeling risk management framework. These policies are defined by common parameters within the model, allowing comparison of system behavior as affected by the policy parameters. The system dynamics model enabled the testing of the potential value of the system dynamics modeling process framework. Results from a fractional factorial designed experiment identified the sensitive parameters that affect the key result measures established to assess model behavior, focusing on timeliness, effectiveness, and quality. The experimental process highlighted the capabilities of system dynamics modeling to provide insight from the model structure, in addition to the system results. These insights supported assessment of the policies that were tested. The proposed modeling process risk management policy delivered results that were substantially better than those of the baseline policy. The simulated project was delivered 26% faster, with 49% fewer rework discovery resources, and 1% higher actual work content in the project. The proposed policy also delivered superior results when compared to other common approaches to system dynamics modeling process risk management. / Ph. D.

The objective of this research is to explore a methodology that can be used for testing and evaluating AVCS technologies, and, in particular, automatic headway control models for trucks operating on rural highways. The emphasis is put on the realization of vehicle headway control in the real world highway systems. System dynamics has been selected as the simulation tool for developing, testing and evaluating vehicle headway control models. The following behavior of human driver in a real world highway environment is studied and simulated. An automatic headway control model, Multiple-mode Vehicle Headway Control (MVHC) model, is developed for single lane, cars and trucks mixed flow control in a rural highway system. Using safety and motorist comfort as MOE criteria and the acceleration noise as the index of motorist comfort, some selected automatic headway control models are evaluated. This study demonstrated that simulation affords a means of modeling control processes with various certain and uncertain factors, and therefore, it plays a key role in the development of automatic headway control systems. / Ph. D.

Complex socioenvironmental problems such as food, energy and water shortages, health impacts from environmental contamination and global climate change present significant challenges to the global community. Addressing these problems will require an interdisciplinary systems-thinking approach that coordinates problem-solving between practitioners of varied disciplines including engineers, physical scientists, economists and other social scientists. Civil and environmental engineers have distinct technical skills necessary to help address these challenges as part of coordinated multidisciplinary efforts towards the achievement of comprehensive and sustainable resolutions to these problems. Ensuring civil and environmental engineers are trained to think and work in this multidisciplinary exchange requires incorporation of systems-thinking into engineering academic curricula. Attempts have been made to incorporate these skill sets into civil and environmental engineering (CEE) coursework. These efforts, as well as evaluation of their effectiveness in training CEE students to think systemically, have lacked in coordination to integrate them as part of the overarching academic curricula. This research advances the current body of knowledge regarding incorporation of systems-thinking into CEE coursework by examining the impacts of system dynamics model based educational tools on systems-thinking learning outcomes of CEE students in a one-semester CEE elective course. The findings suggest that system dynamics modeling can be an effective tool in educating future systems thinkers in the CEE disciplines. / Doctor of Philosophy / Complex socioenvironmental problems such as food, energy and water shortages, health impacts from environmental contamination and global climate change present significant challenges to the global community. Addressing these problems will require an interdisciplinary systems-thinking approach that coordinates problem-solving between practitioners of varied disciplines including engineers, physical scientists, economists and other social scientists. Civil and environmental engineers have distinct technical skills necessary to help address these challenges as part of coordinated multidisciplinary efforts towards the achievement of comprehensive and sustainable resolutions to these problems. Ensuring civil and environmental engineers are trained to think and work in this multidisciplinary exchange requires incorporation of systems-thinking into engineering academic curricula. Attempts have been made to incorporate these skill sets into civil and environmental engineering (CEE) coursework. These efforts, as well as evaluation of their effectiveness in training CEE students to think systemically, have lacked in coordination to integrate them as part of the overarching academic curricula. This research advances the current body of knowledge regarding incorporation of systems-thinking into CEE coursework by examining the impacts of system dynamics model based educational tools on systems-thinking learning outcomes of CEE students in a one-semester CEE elective course. The findings suggest that system dynamics modeling can be an effective tool in educating future systems thinkers in the CEE disciplines.

Infrastructure management must move from a perspective that may singularly emphasize facility condition assessment to a broader view that involves nonphysical factors, which may substantially impact facility performance and shorten its service life. Socioeconomic, technological, regulatory, and user value changes can substantially increase the service expectations of existing facilities. Based on a theoretical framework drawn from prior work, this research develops a new approach to model infrastructure performance and assess factors that influence the remaining service life of highway bridges. Key parameters that impact the serviceability of highway bridges are identified and incorporated into a system dynamics model. This platform supports parametric scenario analysis and is applied in several cases to test how various factors influence bridge service life and performance. This decision support system provides a new approach for modeling serviceability over time and gives decision-makers an indication of: (a) the gap between society's service expectations and the service level provided and (b) the remaining service life of a highway bridge. / Ph. D.