Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 163-177). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 163-177). Also available on the Internet.

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Substantial anthropogenic change of the Earth’s climate is modifying patterns of rainfall, river flow, glacial melt and groundwater recharge rates across the planet, undermining many of the stationarity assumptions upon which water resources infrastructure has been historically managed. This hydrological uncertainty is creating a potentially vast range of possible futures that could threaten the dependability of vital regional water supplies. This, combined with increased urbanisation and rapidly growing regional populations, is putting pressures on finite water resources. One of the greatest international challenges facing decision makers in the water industry is the increasing influences of these “deep” climate change and population growth uncertainties affecting the long-term balance of supply and demand and necessitating the need for adaptive action. Water companies and utilities worldwide are now under pressure to modernise their management frameworks and approaches to decision making in order to identify more sustainable and cost-effective water management adaptations that are reliable in the face of uncertainty. The aim of this thesis is to compare and contrast a range of existing Decision Making Methods (DMMs) for possible application to Water Resources Management (WRM) problems, critically analyse on real-life case studies their suitability for handling uncertainties relating to climate change and population growth and then use the knowledge generated this way to develop a new, resilience-based WRM planning methodology. This involves a critical evaluation of the advantages and disadvantages of a range of methods and metrics developed to improve on current engineering practice, to ultimately compile a list of suitable recommendations for a future framework for WRM adaptation planning under deep uncertainty. This thesis contributes to the growing vital research and literature in this area in several distinct ways. Firstly, it qualitatively reviews a range of DMMs for potential application to WRM adaptation problems using a set of developed criteria. Secondly, it quantitatively assesses two promising and contrasting DMMs on two suitable real-world case studies to compare highlighted aspects derived from the qualitative review and evaluate the adaptation outputs on a practical engineering level. Thirdly, it develops and reviews a range of new potential performance metrics that could be used to quantitatively define system resilience to help answer the water industries question of how best to build in more resilience in future water resource adaptation planning. This leads to the creation and testing of a novel resilience driven methodology for optimal water resource planning, combining optimal aspects derived from the quantitative case study work with the optimal metric derived from the resilience metric investigation. Ultimately, based on the results obtained, a list of suitable recommendations is compiled on how to improve the existing methodologies for future WRM planning under deep uncertainty. These recommendations include the incorporation of more complex simulation models into the planning process, utilisation of multi-objective optimisation algorithms, improved uncertainty characterisation and assessments, an explicit robustness examination and the incorporation of additional performance metrics to increase the clarity of the strategy assessment process.

[pt] Este trabalho tem como objetivos principais a apresentação, análise e síntese de sistemas de controle por realimentação de saídas com características robustas. São consideradas incertezas no modelo do tipo não estruturada ( dinâmica não modelada ) e estruturada ( valores desconhecidos nos parâmetros ), distúrbios ( entradas desconhecidas ) e ruídos no sensor. Ênfase especial é dada ao projeto de sistemas de controle implementados usando observadores de estado, que representam um tipo especial de sistemas de controle por realimentação de saídas. Uma revisão dos principais tipos de observadores é feita, incluíndo observadores robustos com capacidade de rejeição e estimação simultânea de distúrbios, comparando suas características através de um exemplo. Logo após, o sistema resultante, quando observadores de estado são introduzidos na lei de controle, é analisado em presença de incertezas, mostrando a limitação na validade do Princípio da Separação. Técnicas modernas de controle robusto são usadas para melhorar as propriedades de robustez dos sistems de controle, entre elas: Recuperação da Função de Transferência da Malha (LTR) e Controle H-infinito. É mostrado também, que através de uma escolha conveniente dos parâmetros livres do controle LQG, é possível sintetizar controladores robustos. Estas técnicas são usadas para resolver problemas específicos no controle de estruturas flexíveis, incluíndo perturbações na entrada da planta, incertezas paramétricas. As técnicas aplicadas no presente trabalho demonstram eficácia e simplicidade. / [en] This work intends to present an introduction to the analysis and syntesis of output feedback control systems with robust characteristics. They are considered unstructured ans structured model uncertainties, disturbances, unknown inputs and noise. It is given a special emphasys on the control systems which were implemented by the use of state observers, which represents a special type of output feedback control systems. A review of the principais types of observers are done, including robust observers with interesting characteristics such as the capacity of simultaneous rejection and estimation of disturbances, and their features are compared in an example. After that, it is done an analysis of the resultant systems when state observers are introduced in the control system in the presence of uncertainties, showing limitations to apply the Separation Principle. Modern techniques of robust control are used to enhance the properties of robustness of the control systems, such as Loop Transfer Recovery (LTR) technique and H(infinito) control.It is also shown that an adequate choice of the free parameters in the LQC control allows to synthetize robust controllers. These techniques are used to solve specific problems in the control of flexible structures, including disturbances in the plant input, uncertainties caused by unmodeled dynamic in high frequency ( spillover problem ) and parametric uncertainties. The techniques applied in this work show effectiveness and simplicity. / [es] Este trabajo tiene como objetivos principales la presentación, análisis y síntesis de sistemas de control por realimentación de salidas con características robustas. Son consideradas incertidumbres en el modelo del tipo no extructurada (dinámica no modelada) y extructurada (valores desconocidos en los parámetros), distúrbios (entradas desconocidas) y ruidos en el sensor. Se le dedica especial atención al proyecto de sistemas de control que fue implementado utilizando observadores de estado, que representan un tipo especial de sistemas de control por realimentación de salidas. Se realiza una revisión de los principales tipos de observadores, incluyendo observadores robustos con capacidad de rechazo y estimación simultánea de disturbios, comparando sus características a través de un ejemplo. Seguidamente se analiza, en presencia de incertidumbre, el sistema que resulta al introducir observadores de estado en la ley de control, mostrando las limitaciones en la validez del Principio de la Separación. Se utilizan técnicas modernas de control robusto para mejorar las propriedades de robustez de los sistems de control, entre ellas: Recuperación de la Función de Transferencia de la Malla (LTR) y Control H-infinito. Se muestra también, que a través de una selección conveniente de los parámetros libres del control LQG, es posible sintetizar controladores robustos. Estas técnicas se utilizan para resolver problemas específicos en el control de extructuras flexibles, incluyendo perturbaciones en la entrada de la planta e incertidumbres paramétricas. Las técnicas aplicadas en este trabajo demuestran eficiencia y simplicidad.

abstract: In mixture-process variable experiments, it is common that the number of runs is greater than in mixture-only or process-variable experiments. These experiments have to estimate the parameters from the mixture components, process variables, and interactions of both variables. In some of these experiments there are variables that are hard to change or cannot be controlled under normal operating conditions. These situations often prohibit a complete randomization for the experimental runs due to practical and economical considerations. Furthermore, the process variables can be categorized into two types: variables that are controllable and directly affect the response, and variables that are uncontrollable and primarily affect the variability of the response. These uncontrollable variables are called noise factors and assumed controllable in a laboratory environment for the purpose of conducting experiments. The model containing both noise variables and control factors can be used to determine factor settings for the control factor that makes the response "robust" to the variability transmitted from the noise factors. These types of experiments can be analyzed in a model for the mean response and a model for the slope of the response within a split-plot structure. When considering the experimental designs, low prediction variances for the mean and slope model are desirable. The methods for the mixture-process variable designs with noise variables considering a restricted randomization are demonstrated and some mixture-process variable designs that are robust to the coefficients of interaction with noise variables are evaluated using fraction design space plots with the respect to the prediction variance properties. Finally, the G-optimal design that minimizes the maximum prediction variance over the entire design region is created using a genetic algorithm. / Dissertation/Thesis / Ph.D. Industrial Engineering 2010

Este trabalho consiste basicamente na realização do teste de uma gama de variáveis explicativas anuais, oriundas da literatura sobre crescimento econômico, para os estados brasileiros. O objeto primeiro é identificar quais delas são robustas em apresentar relação com as variações do Produto Interno Bruto (PIB) per capita, ou seja, quais se mantêm significativas quando testadas junto a diferentes conjuntos de outras variáveis explicativas. O período analisado compreende os anos de 1986 a 2002. Resende e Figueiredo1 realizaram esse mesmo trabalho utilizando dados decenais entre 1960 e 2000. Assim, um segundo objetivo é comparar os resultados de longo prazo, obtido por Resende e Figueiredo, com os de curto prazo. Para tanto, empregou-se o teste de robustez proposto por Levine e Renelt2, o Extreme Bounds Analysis (EBA), e o teste desenvolvido por Sala-i-Martin3, que argumenta que, em vez de analisar os extremos das estimativas dos coeficientes de uma variável específica, é necessário fazer a análise de toda a distribuição desses coeficientes.Com base nos testes efetuados, conclui-se que, no curto prazo, atividade agrícola, setor de serviços e água encanada têm correlação robusta com as taxas de crescimento do PIB per capita; apesar da atividade agrícola se revelar o fator de maior relação com o crescimento econômico no curto prazo, os dados não demonstraram nenhuma robustez no longo. Quanto à ocorrência de convergência condicional dos PIBs per capita estaduais, esta se confirmou tanto para o curto quanto para o longo prazo. Por outro lado, mortalidade infantil, fecundidade e carga tributária apresentam correlação robusta com as taxas de crescimento do PIB per capita somente no longo prazo. A taxa de urbanização demonstra correlação positiva no curto prazo, mas negativa no longo. / The present work basically consists of examination of a set of explanatory annual variables, whose sort derived from Economic Growth literature, to the Brazilian states. The prime aim is to identify which of those variables presents robust correlation with the per capita Gross Domestic Product (GDP) rates, researching the 1986 to 2002 period. Resende e Figueiredo have done the same work with decennial data between 1960 and 2000. In this way, another aim is comparing those long term results with the short one. In order to do that, one applied the Extreme Bounds Analysis (EBA) test proposed by Levine and Renelt, as well as the test developed by Sala-i-Martin, who argued it is necessary to analyze which and all coefficients, instead of to the extremes only. Based in those tests, one concludes that the variables which present robust correlations with the per capita GDP rates in the short term are farming and service sectors as well canalized water. Although the farming was revealed the main factor of growth in the short term, it did not presented robustness at all in the long term. In the other hand, babyish mortality rate, fertility rate and tax burden presented robust correlation only in the long term. The urban rate showed positive robust correlation in the short term, despite of negative one in the long term.

Dans cette thèse, nous nous intéressons à des chaînes logistiques dont les acteurs de la chaîne sont des entités décisionnelles indépendantes. Plus précisément, notre cadre d’étude sera un "maillon" d’une chaîne logistique (relation client fournisseur) dont les acteurs (le client et le fournisseur) sont des entités décisionnelles indépendantes qui souhaitent mettre en place des processus de planification coopératifs en présence d’incertitude, sachant que le client fabriques des produits à la commande et le fournisseur sur stock. Dans ce contexte, la contribution majeure visée par nos travaux est l’intégration des connaissances imparfaites sur les données (date du besoin en composants, quantité nécessaire…etc.) afin de calculer le plan d’approvisionnement plus robuste (plan minimisant l’impact de l’incertitude). L’intégration des imperfections repose sur l’utilisation de la théorie des possibilités. Une fois le modèle de représentation des données imparfaites réalisé, nous proposons des méthodes de calcul de plan d’approvisionnement utilisant les informations supplémentaires grâce à la représentation des imperfections. / In this thesis, we focus on supply chain where the actors are independent entities. More precisely, ours interests are on point-to-point (customer/supplier) relationships where the actors (the customer and the supplier) are independent entities which want to set up collaborative planning process under uncertainty, such that the customer produces to orders and the supplier produces to stock. In this context, the major contribution of the thesis is the integration of ill-known data (date of requirement, required quantities ...etc.) to calculate a robust procurement plan (plan which minimize the impact of uncertainty). We used the possibility theory to model those uncertainties. After the model of ill-known data proposed, we present a set of methods to compute a procurement plan using the additional information (information on the uncertainty).

La distribution de liquide cryogénique en « vrac », ou par camions citernes, est un cas particulier des problèmes d’optimisation logistique. Ces problèmes d’optimisation de chaines logistiques et/ou de transport sont habituellement traités sous l’hypothèse que les données sont connues à l’avance et certaines. Or, la majorité des problèmes d’optimisation industriels se placent dans un contexte incertain. Mes travaux de recherche s’intéressent aussi bien aux méthodes d’optimisation robuste que stochastiques.Mes travaux portent sur deux problèmes distincts. Le premier est un problème de tournées de véhicules avec gestion des stocks. Je propose une méthodologie basée sur les méthodes d’optimisation robuste, représentant les pannes par des scénarios. Je montre qu’il est possible de trouver des solutions qui réduisent de manière significative l’impact des pannes d’usine sur la distribution. Je montre aussi comment la méthode proposée peut aussi être appliquée à la version déterministe du problème en utilisant la méthode GRASP, et ainsi améliorer significativement les résultats obtenu par l’algorithme en place. Le deuxième problème étudié concerne la planification de la production et d’affectation les clients. Je modélise ce problème à l’aide de la technique d’optimisation stochastique avec recours. Le problème maître prend les décisions avant qu’une panne ce produise, tandis que les problèmes esclaves optimisent le retour à la normale après la panne. Le but est de minimiser le coût de la chaîne logistique. Les résultats présentés contiennent non seulement la solution optimale au problème stochastique, mais aussi des indicateurs clés de performance. Je montre qu’il est possible de trouver des solutions ou les pannes n’ont qu’un impact mineur. / The distribution of liquid gazes (or cryogenic liquids) using bulks and tractors is a particular aspect of a fret distribution supply chain. Traditionally, these optimisation problems are treated under certainty assumptions. However, a large part of real world optimisation problems are subject to significant uncertainties due to noisy, approximated or unknown objective functions, data and/or environment parameters. In this research we investigate both robust and stochastic solutions. We study both an inventory routing problem (IRP) and a production planning and customer allocation problem. Thus, we present a robust methodology with an advanced scenario generation methodology. We show that with minimal cost increase, we can significantly reduce the impact of the outage on the supply chain. We also show how the solution generation used in this method can also be applied to the deterministic version of the problem to create an efficient GRASP and significantly improve the results of the existing algorithm. The production planning and customer allocation problem aims at making tactical decisions over a longer time horizon. We propose a single-period, two-stage stochastic model, where the first stage decisions represent the initial decisions taken for the entire period, and the second stage representing the recovery decision taken after an outage. We aim at making a tool that can be used both for decision making and supply chain analysis. Therefore, we not only present the optimized solution, but also key performance indicators. We show on multiple real-life test cases that it isoften possible to find solutions where a plant outage has only a minimal impact.

This thesis deals with reducing automata, their normalization, and their application for a (robust) reduction analysis and localization of syntactic errors for deterministic context-free languages (DCFL). A reducing automaton is similar to a restarting automaton with two subtle differences: an explicit marking of reduced symbols (which makes it possible to determine a position of an error accurately), and moving a lookahead window inside a control unit (which brings reducing automata closer to devices of classical automata and formal language theory). In case of reducing automata, it is easier to adopt and reuse notions and approaches developed within classical theory, e.g., prefix correctness or automata minimization. For any nonempty deterministic context-free language specified by a monotone reducing automaton, both prefix correct and minimal, we propose a method of robust analysis by reduction which ensures localization of formally defined types of (real) errors, correct subwords, and subwords causing reduction conflicts (i.e., subwords with ambiguous syntactic structure that can be reduced in different words in different ways). We implement the proposed method by a new type of device (called postprefix robust analyzer) and we briefly show how to implement this method by a deterministic pushdown...