L'objet de cette thèse sur les réseaux de capteurs est l'étude du déploiement minimal de capteurs lorsque ceux-ci doivent couvrir un ensemble discret de cibles plutôt que des superficies. Après la présentation des caractéristiques d'un réseau de capteurs, et l'intérêt d'un déploiement minimal, nous en proposons une modélisation en théorie des graphes. Nous présentons ensuite un état de l'art décrivant certaines techniques de résolution par la programmation mathématique de diverses problématiques dans ce type de réseau. Nous utilisons plusieurs programmes linéaires en variables mixtes afin de résoudre le problème du déploiement minimal des capteurs sous des contraintes de couverture de toutes les cibles et de connectivité des capteurs entre eux. Finalement, nous concevons une nouvelle heuristique de calcul de placement de capteurs lorsque les cibles sont placées sur une grille à motif carré et nous conjecturons que cette heuristique retourne une solution optimale dans tous les cas. / The objectif of this thesis on wireless sensor networks is to study the deployment of a minimal number of sensors to cover specific targets instead of continuous areas. After a presentation of the characteristics of wireless sensor networks, and after justifying the interest of an optimal sensor deployment, we propose a graph-theory based model for wireless sensor networks. We then present a state of the art describing various mathematical programming models and resolution techniques regarding a number of optimization problems in such networks. We formulate several Mixed Integer Linear programs to solve the optimal sensor deployment problem under contraints related to the coverage of all targets and connectivity between sensors. Finally, we conceive a new heuristic for sensor placement when targets are placed in a square grid graph, and we conjecture that this heuristic returns an optimal solution in all cases.

No description available.

A Virtualização de Funções de Rede (NFV – Network Function Virtualization) é um novo conceito arquitetural que está remodelando a operação de funções de rede (e.g., firewall, gateways e proxies). O conceito principal de NFV consiste em desacoplar a lógica de funções de rede dos dispositivos de hardware especializados e, desta forma, permite a execução de imagens de software sobre hardware de prateleira (COTS – Commercial Off-The-Shelf). NFV tem o potencial para tornar a operação das funções de rede mais flexíveis e econômicas, primordiais em ambientes onde o número de funções implantadas pode chegar facilmente à ordem de centenas. Apesar da intensa atividade de pesquisa na área, o problema de posicionar e encadear funções de rede virtuais (VNF – Virtual Network Functions) de maneira escalável e com baixo custo ainda apresenta uma série de limitações. Mais especificamente, as estratégias existentes na literatura negligenciam o aspecto de encadeamento de VNFs (i.e., objetivam sobretudo o posicionamento), não escalam para o tamanho das infraestruturas NFV (i.e., milhares de nós com capacidade de computação) e, por último, baseiam a qualidade das soluções obtidas em custos operacionais não representativos. Nesta tese, aborda-se o posicionamento e o encadeamento de funções de rede virtualizadas (VNFPC – Virtual Network Function Placement and Chaining) como um problema de otimização no contexto intra- e inter-datacenter. Primeiro, formaliza-se o problema VNFPC e propõe-se um modelo de Programação Linear Inteira (ILP) para resolvêlo. O objetivo consiste em minimizar a alocação de recursos, ao mesmo tempo que atende aos requisitos e restrições de fluxo de rede. Segundo, aborda-se a escalabilidade do problema VNFPC para resolver grandes instâncias do problema (i.e., milhares de nós NFV). Propõe-se um um algoritmo heurístico baseado em fix-and-optimize que incorpora a meta-heurística Variable Neighborhood Search (VNS) para explorar eficientemente o espaço de solução do problema VNFPC. Terceiro, avalia-se as limitações de desempenho e os custos operacionais de estratégias típicas de aprovisionamento ambientes reais de NFV. Com base nos resultados empíricos coletados, propõe-se um modelo analítico que estima com alta precisão os custos operacionais para requisitos de VNFs arbitrários. Quarto, desenvolve-se um mecanismo para a implantação de encadeamentos de VNFs no contexto intra-datacenter. O algoritmo proposto (OCM – Operational Cost Minimization) baseia-se em uma extensão da redução bem conhecida do problema de emparelhamento ponderado (i.e., weighted perfect matching problem) para o problema de fluxo de custo mínimo (i.e., min-cost flow problem) e considera o desempenho das VNFs (e.g., requisitos de CPU), bem como os custos operacionais estimados. Os resultados alcaçados mostram que o modelo ILP proposto para o problema VNFPC reduz em até 25% nos atrasos fim-a-fim (em comparação com os encadeamentos observados nas infra-estruturas tradicionais) com um excesso de provisionamento de recursos aceitável – limitado a 4%. Além disso, os resultados evidenciam que a heurística proposta (baseada em fix-and-optimize) é capaz de encontrar soluções factíveis de alta qualidade de forma eficiente, mesmo em cenários com milhares de VNFs. Além disso, provê-se um melhor entendimento sobre as métricas de desempenho de rede (e.g., vazão, consumo de CPU e capacidade de processamento de pacotes) para as estratégias típicas de implantação de VNFs adotadas infraestruturas NFV. Por último, o algoritmo proposto no contexto intra-datacenter (i.e. OCM) reduz significativamente os custos operacionais quando comparado aos mecanismos de posicionamento típicos uti / Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. More specifically, existing strategies have neglected the chaining aspect of NFV (focusing on efficient placement only), failed to scale to hundreds of network functions and relied on unrealistic operational costs. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. First, we formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose an Integer Linear Programming (ILP) model to solve it. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. Then, we address scalability of VNFPC problem to solve large instances (i.e., thousands of NFV nodes) by proposing a fixand- optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. Further, we assess the performance limitations of typical NFV-based deployments and the incurred operational costs of commodity servers and propose an analytical model that accurately predict the operational costs for arbitrary service chain requirements. Then, we develop a general service chain intra-datacenter deployment mechanism (named OCM – Operational Cost Minimization) that considers both the actual performance of the service chains (e.g., CPU requirements) as well as the operational incurred cost. Our novel algorithm is based on an extension of the well-known reduction from weighted matching to min-cost flow problem. Finally, we tackle the problem of monitoring service chains in NFV-based environments. For that, we introduce the DNM (Distributed Network Monitoring) problem and propose an optimization model to solve it. DNM allows service chain segments to be independently monitored, which allows specialized network monitoring requirements to be met in a efficient and coordinated way. Results show that the proposed ILP model for the VNFPC problem leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Also, we provide strong evidences that our fix-and-optimize based heuristic is able to find feasible, high-quality solutions efficiently, even in scenarios scaling to thousands of VNFs. Further, we provide indepth insights on network performance metrics (such as throughput, CPU utilization and packet processing) and its current limitations while considering typical deployment strategies. Our OCM algorithm reduces significantly operational costs when compared to the de-facto standard placement mechanisms used in Cloud systems. Last, our DNM model allows finer grained network monitoring with limited overheads. By coordinating the placement of monitoring sinks and the forwarding of network monitoring traffic, DNM can reduce the number of monitoring sinks and the network resource consumption (54% lower than a traditional method).

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No. of bitstreams: 1 nahuis_fvc_dr_ilha.pdf: 2994686 bytes, checksum: 5e487b40d4aeb0006f40a0abdb9d9af6 (MD5) Previous issue date: 2017-02-17 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Nesta tese são apresentados três modelos de programação matemática que abordam os problemas de otimização relacionados ao gerenciamento da energia nos sistemas de distribuição de energia elétrica (SDEE), como: 1) Programação ótima das entregas e carregamento dos veículos elétricos (VEs) durante a navegação em um mapa de cidade, 2) Gerenciamento ótimo pelo lado da demanda considerando um sistema fotovoltaico híbrido (SFH) em uma residência em baixa tensão (RBT) no SDEE, e 3) O melhoramento do fator de carga (FC) do SDEE através do controle da demanda. O primeiro problema visa minimizar os custos relacionados com a manutenção e geração de horas extra durante a operação de uma frota de VEs, levando em conta um conjunto de entregas pre-especificadas, assim como, pontos de carregamento alocados ao longo de cada via urbana (principal e/ou secundária) pertencente ao mapa da cidade. No segundo problema, para uma residência em baixa tensão é planejado um perfil ótimo de consumo para o dia seguinte. Este perfil de consumo é obtido através de um programa de gerenciamento pelo lado da demanda (GLD) que considera uma estrutura tarifária e um esquema de operação que otimiza os recursos energéticos vindos de um SFH e o SDEE. Para cada problema de otimização é apresentado o seu correspondente modelo de programação não linear inteiro misto (PNLIM). O terceiro problema visa minimizar os custos por compra de energia (consumo e perdas de potência ativa) da concessionária, levando em conta, o controle da demanda dos usos-finais, presentes nas unidades consumidoras (residenciais, comerciais, e industriais) no SDEE. As incertezas na utilização dos usos-finais nas unidades consumidoras são simuladas através de um algoritmo Monte Carlo. Além disso, o modelo proposto PIMRQ é rodado dentro de um processo iterativo, que visa a melhoria do FC do SDEE. Por outro lado, através destes modelos não-lineares, a solução ótima global não é garantida, enquanto o uso de modelos equivalentes (para o primeiro e segundo problema, sendo um modelo aproximado para o terceiro) de programação linear inteira mista (PLIM) resolvidos por ferramentas de otimização clássica existentes garantem a convergência para a solução ótima global. Por conseguinte, para resolver este inconveniente, os seus modelos MILP equivalentes são obtidos e explicados em detalhe. Os modelos propostos foram implementados na linguagem de modelagem algébrica AMPL e resolvidos usando o solver comercial CPLEX. Além disso, algoritmos de simulação para representar as incertezas dos tempos de demora na operação dos VEs e os hábitos de utilização dos usos-finais durante o dia, são desenvolvidos. Um grafo unidirecional de 71 nós, uma rede elétrica IEEE de 34 nós, e 21 usos-finais (incluído um VE plug-in para o carregamento na residência) residenciais são utilizados para testar a precisão e a eficiência, assim como, também técnica de solução dos modelos propostos para cada problema. / This thesis presents three mathematical programming models to address the optimization problems related to the energy management in the electricity distribution systems (EDSs), such as: 1) Optimal delivery scheduling and charging of electric vehicles (EVs) in the navigation of a city map, 2) Optimal demand side management of an EDS considering a hybrid photovoltaic system (HPS) in a residential low voltage (RLV), and 3) Load factor improvement through the demand control in the EDS. The first problem aims at minimizing the costs related to the maintenance and generation of extra hours during the operation of a EVs fleet, taking into account a number of prespecified deliveries, as well as charging points allocated along each urban road (main or secondary) belongs to the city map. In the second problem, for a RLV, an optimal consumption profile of a day-ahead is planned. This consumption profile is obtained through a demand side management (DSM) program that considers a tariff structure and an operating scheme that optimizes the energy resources coming from HFS and EDS. The third problem aims at minimizing the costs of energy purchase (consumption and active energy losses) of the company, taking into account, the demand control of the end-uses, presents in the consumers units (residential, commercial, and industrial) in the EDS. Uncertainties in the use of the end-uses in the different consumer units are simulated through a Monte Carlo algorithm that determines a habitual consumption profile for EDSs. Based on this habitual profile, the proposed MIPRQ model determines an optimal profile for EDSs. This model uses an iterative process that aims to improve the load factor of the EDS. For each optimization problem the corresponding non-linear mixed integer programming (NLMIP) model is presented. On the other hand, via these nonlinear models, the global optimal solution is not guaranteed, while using the equivalent mixed-integer linear (MILP) models (for the first and second problems, being an approximate model for the third) and solving them by existing classical optimization tools ensures convergence to global optimal solution. Therefore, in order to address this drawback, their equivalent mixed integer linear programming (MILP) models are obtained and explained in detail. The proposed models are implemented in the algebraic modeling language AMPL and solved using the commercial CPLEX solver. Moreover, simulations algorithms to represent the uncertainties of delay times in the operation of EVs and usage habits of end-uses during the day, are developed. A multidirectional graph with 71 nodes, an electrical network IEEE 34 nodes, and a quantity of 21 residential end-uses (including an EV plug-in for residential charging) are used to test the precision and the efficiency, as well as the solution technique of the models proposed for each problem. / CNPq: 141462/2013- 2

Layout Decision Analysis and Design is a ubiquitous problem in a variety of work domains that is important from both strategic and operational perspectives. It is largely a complex, vague, difficult, and ill-structured problem that requires intelligent and sophisticated decision analysis and design support. <br /><br /> Inadequate information availability, combinatorial complexity, subjective and uncertain preferences, and cognitive biases of decision makers often hamper the procurement of a superior layout configuration. Consequently, it is desirable to develop an intelligent decision support system for layout design that could deal with such challenging issues by providing efficient and effective means of generating, analyzing, enumerating, ranking, and manipulating superior alternative layouts. <br ><br /> We present a research framework and a functional prototype for an interactive Intelligent System for Decision Support and Expert Analysis in Multi-Attribute Layout Optimization (IDEAL) based on soft computing tools. A fundamental issue in layout design is efficient production of superior alternatives through the incorporation of subjective and uncertain design preferences. Consequently, we have developed an efficient and Intelligent Layout Design Generator (ILG) using a generic two-dimensional bin-packing formulation that utilizes multiple preference weights furnished by a fuzzy Preference Inferencing Agent (PIA). The sub-cognitive, intuitive, multi-facet, and dynamic nature of design preferences indicates that an automated Preference Discovery Agent (PDA) could be an important component of such a system. A user-friendly, interactive, and effective User Interface is deemed critical for the success of the system. The effectiveness of the proposed solution paradigm and the implemented prototype is demonstrated through examples and cases. <br /><br /> This research framework and prototype contribute to the field of layout decision analysis and design by enabling explicit representation of experts? knowledge, formal modeling of fuzzy user preferences, and swift generation and manipulation of superior layout alternatives. Such efforts are expected to afford efficient procurement of superior outcomes and to facilitate cognitive, ergonomic, and economic efficiency of layout designers as well as future research in related areas. <br /><br /> Applications of this research are broad ranging including facilities layout design, VLSI circuit layout design, newspaper layout design, cutting and packing, adaptive user interfaces, dynamic memory allocation, multi-processor scheduling, metacomputing, etc.

Layout Decision Analysis and Design is a ubiquitous problem in a variety of work domains that is important from both strategic and operational perspectives. It is largely a complex, vague, difficult, and ill-structured problem that requires intelligent and sophisticated decision analysis and design support. <br /><br /> Inadequate information availability, combinatorial complexity, subjective and uncertain preferences, and cognitive biases of decision makers often hamper the procurement of a superior layout configuration. Consequently, it is desirable to develop an intelligent decision support system for layout design that could deal with such challenging issues by providing efficient and effective means of generating, analyzing, enumerating, ranking, and manipulating superior alternative layouts. <br ><br /> We present a research framework and a functional prototype for an interactive Intelligent System for Decision Support and Expert Analysis in Multi-Attribute Layout Optimization (IDEAL) based on soft computing tools. A fundamental issue in layout design is efficient production of superior alternatives through the incorporation of subjective and uncertain design preferences. Consequently, we have developed an efficient and Intelligent Layout Design Generator (ILG) using a generic two-dimensional bin-packing formulation that utilizes multiple preference weights furnished by a fuzzy Preference Inferencing Agent (PIA). The sub-cognitive, intuitive, multi-facet, and dynamic nature of design preferences indicates that an automated Preference Discovery Agent (PDA) could be an important component of such a system. A user-friendly, interactive, and effective User Interface is deemed critical for the success of the system. The effectiveness of the proposed solution paradigm and the implemented prototype is demonstrated through examples and cases. <br /><br /> This research framework and prototype contribute to the field of layout decision analysis and design by enabling explicit representation of experts? knowledge, formal modeling of fuzzy user preferences, and swift generation and manipulation of superior layout alternatives. Such efforts are expected to afford efficient procurement of superior outcomes and to facilitate cognitive, ergonomic, and economic efficiency of layout designers as well as future research in related areas. <br /><br /> Applications of this research are broad ranging including facilities layout design, VLSI circuit layout design, newspaper layout design, cutting and packing, adaptive user interfaces, dynamic memory allocation, multi-processor scheduling, metacomputing, etc.

伴隨著永續發展思潮之興起，「大眾運輸導向發展（Transit-oriented development, TOD）」已成為都市規劃之重要理念。相關研究雖曾就TOD緊密、混合使用發展帶來之永續效益進行探討，然高密度之發展模式亦會加速都市內資源消耗，並影響生活環境品質。為解決前述課題，相關文獻因而提出「綠色大眾運輸導向發展（Green transit-oriented development, Green TOD）」理念，以期待在TOD與綠色都市主義（Green urbanism）之結合下，形塑更為友善環境發展之都市型態。國內外雖有相關研究對Green TOD之規劃理念進行探討，並建立評估架構與準則，然規劃上仍未以該理念建構土地使用規劃模式，以協助規劃者研擬規劃方案；此外傳統土地使用規劃模式建構亦較少將土地使用配置現況與變更限制納入考量，規劃模式因而無法反映實際之規劃問題，並使其應用受到限制。 　　基此，本研究係由通盤檢討面向切入建構「綠色大眾運輸導向土地使用規劃模式」，規劃上並以高密度發展、混合使用配置、親生物開放空間追求、非機動運具可及性提升、停車需求抑制、資源配置效益追求、都市機能健全發展為追求目標建構多目標規劃模式；模式考量限制則包含通盤檢討變更可行性、配置區位限制、規模與容量限制、預算限制、運輸場站自明性、自行車道連續性等；模式求解則修正最小偏差法，並設定不同之權重組合尋求非劣解集合；最後則模擬實例情境設計假想例，以測試模式之可用性，並透過敏感度分析探討規劃模式之應用特性。 　　研究結果發現，規劃模式部分目標因追求方向相同而不具有償付關係，然各目標規劃理念、衡量面向與決策內容皆有不同，規劃上因而有保留之必要性，規劃模式並可依據此特性追求整合性之規劃效益，且著重高密度發展策略之應用。而敏感度分析則顯示，預算額度多寡將影響模式之規劃彈性與償付關係之表現程度，規劃前應妥善分析土地使用配置現況後編列適當之預算資源，以確保規劃偏好達成。本研究建構之土地使用規劃模式可於Green TOD 理念下研提不同之替選方案，並輔助規劃單位進行土地使用、自行車路網、水資源配置之規劃作業。 / Transit-oriented development (TOD) has become a main concept of urban planning as the advocacy of sustainable development. Previous studies, though, have explored the benefit of TOD which features of compact development and mixed land use, excessive density would also accelerate the resources consumption in inner city and decrease the quality of living environment. To solve the aforementioned problems, studies have proposed the concept of “Green transit-oriented development (Green TOD)”, which combines the concepts of “TOD” and “Green Urbanism” in anticipation of shaping an environmentally friendly urban form. However, most of the studies about Green TOD mainly focus on defining the planning concept or establishing the evaluation framework and criteria of it, it still lacks a land use planning model for Green TOD which aims to generate planning alternatives objectively for planners. With regard to the land use planning model, prior studies seldom took the current zoning and rezoning restriction into consideration during the model formulation, which not only made the formulated model fail to represent the real planning problem but also decrease the application value. This study, therefore, develops a multi-objective land use planning model for Green TOD from the aspect of overall review of urban planning. The objectives of the model include “maximizing the development density”, “maximizing the mixed land use degree”, “maximizing the biophilic open space”, “maximizing the accessibility of non-motorized vehicle”, “minimizing the parking demand”, “maximizing the benefit of resource allocation” and “minimizing the rezoning scale of available land”. The constrains of the model include “the rezoning feasibility of overall review”, “the restriction of allocated location”, “the allocated restriction of minimum scale and maximum volume”, “budget limitation”, “identification of transit station area” and “connectivity of bikeway network”. The revised minimum deviation method with different weight settings was used to search the non-inferior solutions set for the simulated case to verify the applicability of the developed model. Besides, sensitivity analysis was used to explore the model characteristic. The result found that some of the objectives, which cannot be integrated due to the difference of planning concept, assessing aspect and decision contents, feature of non-trade-off relationship due to the same pursuing direction. The application of the model can therefore apply this characteristic to pursue the integrated benefit accordingly and focus on the planning approach of high density development. Besides, the sensitivity analysis showed that budget amount influences the planning flexibility and trade-off degree significantly. Budgeting should therefore be dealt appropriately after analyzing the current zoning to ensure the achievement of planning preference. The land use planning model developed by this study can be applied to generate planning alternatives under the planning concept of Green TOD and support the authorities for land use allocation, bikeway design and water resource allocation.

From the Proceedings of the 1976 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 29-May 1, 1976, Tucson, Arizona / The case study of an Upper San Pedro River watershed is developed to show how a multiple objective approach to decision-making may be used in watershed management. The effects of various land treatments and management practices on water runoff, sediment, recreation,, wildlife levels, and commercial potential of a study area are investigated while observing constraints' on available land and capital. The example involves the optimization of five objective functions subject to eighteen constraints. In an iterative manner, the decision-maker proceeds from one noninferior solution to another, comparing sets of land management activities for reaching specified goals, and evaluating trade-offs between individual objective functions. This technique, which involves the formulation of a surrogate objective function and the use of the cutting plane method to solve the general nonlinear problem, hopefully provides a compromise between oversimplified and computationally intractable approaches to multiobjective watershed management.

Rapidly assembled tent structures are temporary enclosures used to house people or goods. Their uses vary to include recreation, refugee housing, and military shelters. The structural concepts applied in these shelters are as variable as their uses. Some make use of a tensioned fabric and pole system to provide structural strength. Others have a load-bearing frame with attached fabric skin. Further variants make use of inflatable arches or consist of modular containers. Analysis of a number of different types of rapidly assembled tent structures reveals an area where innovation can occur. Conflicts in the last ten years suggest that rapidly assembled shelters for both military purposes and humanitarian relief have the greatest need for innovative solutions. Existing shelters used by the military lack the versatility and speed of deployment necessary in modern conflict. The lack of scalability in the designs makes it difficult to use an existing tent in different situations. They are slow to construct, heavy, and difficult to transport in large numbers. These problems suggest that there is a need for new shelters that better meet the needs of the military. The application of deployable structures technology meets military's needs for structures with the advantages of a small compacted volume, rapid assembly, and ease of deployment. This makes them ideal for application to shelter structures. The aim of this dissertation was to develop a new type of deployable, long-span shelter frame based upon tiled Bennett mechanisms. An overlapping combination of equilateral Bennett mechanisms yields a structure that opens into a half-cylinder shape, providing an enclosed space useful and applicable to the problem of deployable shelters. The specific application considered in the design portion of this process will be a long-span deployable shelter capable of housing military helicopters. This report details the development of the Bennett Shelter concept. Its deployed and compacted geometries are explored, and a procedure for determining structural properties and dimensions is presented. The full concept for the structure, from outer covering to foundation support is then detailed. Loads affecting the structure are determined, and the process of modelling and analysing the structure is then considered. Optimisation of the structure with respect to weight and serviceability requirements is conducted using a number of different materials, and full analysis of the optimal geometries is completed. As no method exists for evaluating the effect of imperfections on the deployment of overconstrained mechanisms, a procedure is derived. The effects of manufacturing imperfections on deployment of the Bennett mechanism are then explored using the method. A full examination of the variation of energy within the Bennett Shelter during deployment provides valuable insight into the performance of the structure. With the above analysis complete, it is shown that the Bennett Shelter is viable as a long-span deployable shelter.

La crescente attenzione riguardo l’interconnessione tra agricoltura e aspetti ambientali così come la crescita di volatilità dei prezzi dei prodotti agricoli ha posto una nuova enfasi sull’introduzione di misure ambientali nella politiche agricole e sulla ricerca di nuovi strumenti di stabilizzazione del reddito degli agricoltori. La ricerca di questa tesi di dottorato si inserisce in questo contesto e analizza i contratti agro-ambientali, misure della Politica Agricola Comunitaria (PAC) in Unione Europea (UE), sotto una duplice prospettiva. Il primo lavoro di ricerca consiste in un’analisi degli effetti dell’adesione a tali contratti sulle scelte produttive e sulle perfomance economiche degli agricoltori in cinque Paesi dell’UE. I risultati indicano un’eterogeneità di questi effetti: in alcuni Paesi i contratti agro-ambientali sembrano essere più efficaci nel promuovere pratiche agricole sostenibili, così come in alcuni Paesi il pagamento compensativo agro-ambientale sembra non essere sufficiente a compensare la perdita di reddito dei partecipanti. Questo studio è stato condotto combinando il Propensity Score Matching con lo stimatore Difference-in-Differences. Il secondo lavoro di ricerca sviluppa una nuova proposta metodologica che incorpora il rischio in un framework di Programmazione Matematica Positiva (PMP). Il modello elaborato presenta caratteri innovativi rispetto alla letteratura sull’argomento e permette di stimare simultaneamente i prezzi ombra delle risorse, la funzione di costo non lineare dell’azienda agricola e un coefficiente di avversione al rischio specifico per ciascuna azienda. Il modello è stato applicato a tre campioni di aziende e i risultati delle stime testano la calibrazione del modello e indicano valori del coefficiente di avversione al rischio coerenti con la letteratura. Infine il modello è stato impiegato nella simulazione di diversi scenari al fine di verificare il ruolo potenziale di un contratto agro-ambientale come strumento di gestione del rischio a diversi livelli di volatilità dei prezzi agricoli. / The increasing attention to the relationship between agriculture and the environment and the rise in price volatility on agricultural markets has led to a new emphasis on agri-environmental policies as well as to a search for new risk management strategies for the farmer. The research objective of this PhD thesis is in line with this challenging context, since it provides an analysis of the EU agri-environmental schemes (AESs) from two viewpoints. First, an ex-post analysis aims at investigating the AESs for their traditional role as measures which encourage sustainable farming while compensating the farmer for the income foregone in five EU Member States. The effects of AESs participation on farmer’s production plans and economic performances differs widely across Member States and in some of them the environmental payment is not enough to compensate the income foregone of participants. This study has been performed by applying a semi-parametric technique which combines a Difference-in-Differences estimator with a Propensity Score Matching estimator. The second piece of research develops a new methodological proposal to incorporate risk into a farm level Positive Mathematical Programming (PMP) model. The model presents some innovations with respect to the previous literature and estimates simultaneously the resource shadow prices, the farm non-linear cost function and a farm-specific coefficient of absolute risk aversion. The proposed model has been applied to three farm samples and the estimation results confirm the calibration ability of the model and show values for risk aversion coefficients consistent with the literature. Finally different scenarios have been simulated to test the potential role of an AES as risk management tool under different scenarios of crop price volatility.