Banca: Linda Lee Ho / Banca: José Luiz Contador / Banca: João Roberto Ferreira / Banca: José Arnaldo Barra Montevechi / Bancs: Antonio Fernando Branco Costa / Resumo: A docente analisa sua produção científica, enfatizando as pesquisas realizadas após o seu doutorado, concluído em 2009. Trata-se de uma série de 17 artigos versando sobre gráficos de controle para o monitoramento de processos univariados e multivariados. Com relação à processos univariados, a docente investigou o desempenho dos gráficos de controle autocorrelacionados e também com regras especiais de decisão. Com relação à processos multivariados, propôs novas estatísticas para o monitoramento do vetor de médias e/ou da matriz de covariâncias e, mais recentemente, vem investigando o desempenho dos gráficos de controle para o monitoramento de processos multivariados autocorrelacionados, com e sem regras especiais de decisão / Abstract: The author analysis yours scientific production, focusing on the research published after the conclusion of her doctorate, in 2009. It is a set of 17 articles about control charts for monitoring univariate and multivariate processes. Regarding univariate processes, the author investigated the performance of autocorrelated control charts and control charts with special runs rules. Regarding multivariate processes, the author proposed new statistics for monitoring the mean vector and/or the covariance matrix, and recently, has been investigating the performance of the control charts for monitoring multivariate autocorrelated processes, with or without special runs rules

Energy efficiency stands out with its potential to address a number of challenges that today's electric utilities face, including increasing and changing electricity demand, shrinking operating capacity, and decreasing system reliability and flexibility. Being the least cost and least risky alternative, the share of energy efficiency programs in utilities' energy portfolios has been on the rise since the 1980s, and their increasing importance is expected to continue in the future. Despite holding great promise, the ability to determine and invest in only the most promising program alternatives plays a key role in the successful use of energy efficiency as a utility-wide resource. This issue becomes even more significant considering the availability of a vast number of potential energy efficiency programs, the rapidly changing business environment, and the existence of multiple stakeholders. This dissertation introduces hierarchical decision modeling as the framework for energy efficiency program planning in electric utilities. The model focuses on the assessment of emerging energy efficiency programs and proposes to bridge the gap between technology screening and cost/benefit evaluation practices. This approach is expected to identify emerging technology alternatives which have the highest potential to pass cost/benefit ratio testing procedures and contribute to the effectiveness of decision practices in energy efficiency program planning. The model also incorporates rank order analysis and sensitivity analysis for testing the robustness of results from different stakeholder perspectives and future uncertainties in an attempt to enable more informed decision-making practices. The model was applied to the case of 13 high priority emerging energy efficiency program alternatives identified in the Pacific Northwest, U.S.A. The results of this study reveal that energy savings potential is the most important program management consideration in selecting emerging energy efficiency programs. Market dissemination potential and program development and implementation potential are the second and third most important, whereas ancillary benefits potential is the least important program management consideration. The results imply that program value considerations, comprised of energy savings potential and ancillary benefits potential; and program feasibility considerations, comprised of program development and implementation potential and market dissemination potential, have almost equal impacts on assessment of emerging energy efficiency programs. Considering the overwhelming number of value-focused studies and the few feasibility-focused studies in the literature, this finding clearly shows that feasibility-focused studies are greatly understudied. The hierarchical decision model developed in this dissertation is generalizable. Thus, other utilities or power systems can adopt the research steps employed in this study as guidelines and conduct similar assessment studies on emerging energy efficiency programs of their interest.

Abstract not available

Sustainability concerns are increasingly shaping customers' behavior as well as companies' strategy. In this context, optimizing the supply chain with sustainability considerations is becoming a critical issue. However, work with quantitative models is still scarce. Our research contributes by revisiting classical inventory models taking sustainability concerns into account. We believe that reducing all aspects of sustainable development to a single objective is not desirable. We thus reformulate single and multi-echelon economic order quantity models as multi-objective problems. These models are then used to study several options such as buyer-supplier coordination or green technology investment. We also consider that firms are becoming increasingly proactive with respect to sustainability. We thus propose to apply multiple criteria decision aid techniques instead of considering sustainability as a constraint. In this sense, the firm may provide preference information about economic, environmental and social tradeoffs and quickly identify a satisfactory solution.

Flexible approaches for eliciting preferences of decision makers involved in a conflict are developed along with applications to real-world disputes. More specifically, two multiple criteria decision making approaches are proposed for capturing the relative preferences of a decision maker participating in a conflict situation. A case study in logistics concerned with the conflict arising over the expansion of port facilities on the west coast of North America as well as a transportation negotiation dispute are used to illustrate how these approaches can be integrated with the Graph Model for Conflict Resolution, a practical conflict analysis methodology. Ascertaining the preferences of the decision makers taking part in a conflict constitutes a key element in the construction of a formal conflict model. In practice, the relative preferences, which reflect each decision maker’s objectives or goals in a given situation, are rather difficult to obtain. The first method for preference elicitation is to integrate an Analytic Hierarchy Process (AHP) preference ranking method with the Graph Model for Conflict Resolution. The AHP approach is used to elicit relative preferences of decision makers, and this preference information is then fed into a graph model for further stability analyses. The case study of the Canadian west coast port congestion conflict is investigated using this integrated model. Another approach is based on a fuzzy multiple criteria out-ranking technique called ELECTRE III. It is also employed for ranking states or possible scenarios in a conflict from most to least preferred, with ties allowed, by the decision maker according to his or her own value system. The model is applied to a transportation negotiation dispute between the two key parties consisting of shippers and carriers.

Flexible approaches for eliciting preferences of decision makers involved in a conflict are developed along with applications to real-world disputes. More specifically, two multiple criteria decision making approaches are proposed for capturing the relative preferences of a decision maker participating in a conflict situation. A case study in logistics concerned with the conflict arising over the expansion of port facilities on the west coast of North America as well as a transportation negotiation dispute are used to illustrate how these approaches can be integrated with the Graph Model for Conflict Resolution, a practical conflict analysis methodology. Ascertaining the preferences of the decision makers taking part in a conflict constitutes a key element in the construction of a formal conflict model. In practice, the relative preferences, which reflect each decision maker’s objectives or goals in a given situation, are rather difficult to obtain. The first method for preference elicitation is to integrate an Analytic Hierarchy Process (AHP) preference ranking method with the Graph Model for Conflict Resolution. The AHP approach is used to elicit relative preferences of decision makers, and this preference information is then fed into a graph model for further stability analyses. The case study of the Canadian west coast port congestion conflict is investigated using this integrated model. Another approach is based on a fuzzy multiple criteria out-ranking technique called ELECTRE III. It is also employed for ranking states or possible scenarios in a conflict from most to least preferred, with ties allowed, by the decision maker according to his or her own value system. The model is applied to a transportation negotiation dispute between the two key parties consisting of shippers and carriers.

The use of architectures for the design, development, and documentation of system-of-systems engineering has become a common practice in recent years. At the same time, acquisition guidance has been recently reformed to move from the bottom-up approach of the Requirements Generation System (RGS) to the top-down approach mandated by the Joint Capabilities Integration and Development System (JCIDS), which requires the use of DoDAF to support acquisition. Defense agencies have had difficulty adjusting to these new policies, and are struggling to determine how to meet new acquisition requirements. This research has developed the Architecture-based Technology Evaluation and Capability Tradeoff (ARCHITECT) Methodology to respond to these challenges and address concerns raised about the defense acquisition process. The methodology integrates existing tools and techniques for systems engineering and system of systems engineering with several new modeling and simulation tools and techniques developed as part of this research to fill gaps noted in prior CBAs. Additional criteria for the methodology were developed by leveraging lessons learned from similar fields, including management science and cognitive psychology. A suppression of enemy air defenses (SEAD) mission is used to demonstrate the application of ARCHITECT and to show the plausibility of the approach. Overall, it is shown that the ARCHITECT methodology results in an improvement over current CBAs in the criteria developed here.

An Architecture Real Options Complexity-Based Valuation Methodology (ARC-VM) is developed for use to aid in the acquisition of military systems-of-systems (SoS). ARC-VM is suitable for acquisition-level decision making, where there is a stated desire for more informed tradeoffs between cost, schedule, and performance during the early phases of design. First, a framework is introduced to measure architecture complexity as it directly relates to military SoS. Development of the framework draws upon a diverse set of disciplines, including Complexity Science, software architecting, measurement theory, and utility theory. Next, a Real Options based valuation strategy is developed using techniques established for financial stock options that have recently been adapted for use in business and engineering decisions. The derived complexity measure provides architects with an objective measure of complexity that focuses on relevant complex system attributes. These attributes are related to the organization and distribution of SoS functionality and the sharing and processing of resources. The use of Real Options provides the necessary conceptual and visual framework to quantifiably and traceably combine measured architecture complexity, time-valued performance levels, as well as programmatic risks and uncertainties. An example suppression of enemy air defenses (SEAD) capability demonstrates the development and utility of the resulting architecture complexity&Real Options based valuation methodology. Different portfolios of candidate system types are used to generate an array of architecture alternatives that are then evaluated using an engagement model. This performance data is combined with both measured architecture complexity and programmatic data to assign an acquisition value to each alternative. This proves useful when selecting alternatives most likely to meet current and future capability needs.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 164-175). Also available on the Internet.

Thesis supervisor: Michael S. Lewis-Beck. Thesis supervisor: David Redlawsk. Includes bibliographic references (p. 187-195).