Το πρόβλημα εύρεσης συντομότερων διαδρομών είναι ένα από τα πιο θεμελιώδη προβλήματα μονοκριτηριακής βελτιστοποίησης σε δίκτυα. Σε αυτό το πρόβλημα αναζητείται η συντομότερη διαδρομή μεταξύ δύο δεδομένων σημείων ελαχιστοποιώντας ένα κριτήριο κόστους. Σε πολλές εφαρμογές ωστόσο, μας ενδιαφέρουν περισσότερα από ένα κριτήρια προς βελτιστοποίηση. Για παράδειγμα, στην εύρεση διαδρομών σε ένα οδικό δίκτυο με διόδια, μας ενδιαφέρει εκτός από την διανυμένη απόσταση και η ελαχιστοποίηση του χρόνου και του κόστους. Παρόμοια παραδείγματα βρίσκουμε και στον χώρο των δικτύων τηλεπικοινωνιών, όπου εξετάζονται κριτήρια όπως η καθυστέρηση, η πιθανότητα λάθους, ο αριθμός συνδέσμων και άλλα. Σε αυτές τις περιπτώσεις η καλύτερη λύση δεν μπορεί να οριστεί με μονοσήμαντο τρόπο, και συνεπώς καταφεύγουμε σε αντισταθμίσεις μεταξύ των παραγόντων, που είναι γνωστές ως σύνολο λύσεων κατά Pareto. Παρόλο που για το πρόβλημα μονοκριτηριακής εύρεσης συντομότερων διαδρομών υπάρχουν πολλοί αποδοτικοί αλγόριθμοι για την επίλυση του προβλήματος, το αντίστοιχο πολυκριτηριακό πρόβλημα είναι πολύ πιο σύνθετο. Μέχρι τώρα, αυτό το πρόβλημα έχει αποδειχθεί ότι είναι NP-πλήρες. Επιπλέον, έχει αποδειχθεί ότι το πλήθος των λύσεων σε αυτό το πρόβλημα αυξάνεται εκθετικά σε σχέση με το μέγεθος της εισόδου. Υπάρχουν δύο βασικές προσεγγίσεις επίλυσης τέτοιων προβλημάτων, όπου εξετάζονται πολλαπλά κριτήρια. α) Η πρώτη μέθοδος βρίσκει προσεγγιστικές λύσης κατά έναν ορισμένο παράγοντα. Οι προσεγγιστικές μέθοδοι δεν βρίσκουν απαραίτητα ακριβείς λύσεις, αλλά είναι σχετικά γρήγορες και προσφέρουν εγγύηση για το ποσοστό απόκλισης από την βέλτιστη λύση. β) Η δεύτερη μέθοδος χρησιμοποιεί ευρετικές βελτιώσεις για να επιταχύνει τους ήδη υπάρχοντες αλγορίθμους. Τέτοιες τεχνικές βρίσκουν ακριβείς λύσεις, και το ζητούμενο είναι να επιτευχθεί μια πολύ καλή χρονική απόδοση. Στην παρούσα διπλωματική εργασία επικεντρωνόμαστε στην δεύτερη μέθοδο, υποκινούμενοι από την μεγάλη ζήτηση πρακτικών εφαρμογών για εύρεση αποτελεσματικής και ακριβούς λύσης του προβλήματος συντομότερων διαδρομών υπό πολλαπλά κριτήρια. Πιο συγκεκριμένα, στην εργασία αυτή παρουσιάζουμε ένα ενοποιημένο πλαίσιο για την αποδοτική επίλυση αυτών των προβλημάτων. Προτείνουμε νέες μεθόδους ή βελτιώσεις των υπαρχόντων. Υλοποιήσαμε τις μεθόδους που παρουσιάζουμε συνοδεύοντάς τις με μια εκτενή πειραματική μελέτη πάνω σε δίκτυα ευρείας κλίμακας. / We present new implementations of heuristic algorithms for the solution of the multiobjective shortest path problem, using a new graph structure specifically suited for large scale road networks. We enhance the heuristics with further optimizations and experimentally evaluate the performance of our enhanced implementation on real world road networks achieving 10 times better performance with respect to the best previous study.

Thesis (MComm)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: In a ground-based air defense (GBAD) military environment, defended assets on the ground require protection from enemy aircraft entering the defended airspace. These aircraft are detected by means of a network of sensors and protection is afforded by means of a pre-deployment of various ground-based weapon systems. A fire control officer is responsible for deciding upon an assignment of weapon systems to those aircraft classified as threats. The problem is therefore to find the best set of weapon systems to assign to the threats, based on some pre-specified criterion or set of criteria. This problem is known as the weapon assignment problem. The conditions under which the fire control officer has to operate are typically extremely stressful. A lack of time is a severely constraining factor, and the fire control officer has to propose an assignment of weapon systems to threats based on his limited knowledge and intuition, with little time for analysis and no room for error. To aid the fire control officer in this difficult decision, a computerised threat evaluation and weapon assignment (TEWA) decision support system is typically employed. In such a decision support system a threat evaluation subsystem is responsible for classifying aircraft in the defended airspace as threats and prioritising them with respect to elimination, whereas a weapon assignment subsystem is responsible for proposing weapon assignments to engage these threats. The aim in this thesis is to model the weapon assignment problem as a multiobjective decision problem. A list of relevant objectives is extracted by means of feedback received from a weapon assignment questionnaire which was completed by a number of military experts. By using two of these objectives, namely the cost of assigning weapon systems and the accumulated single shot hit probability, for illustrative purposes, a bi-objective weapon assignment model is derived and solved by means of three multiobjective optimisation methodologies from the literature in the context of a simulated, but realistic, GBAD scenario. The analytic hierarchy process (AHP) is implemented by means of assessments carried out in conjunction with a military expert. The assignment of weapon systems to threats is achieved by means of a greedy assignment heuristic and an AHP assignment model. Both these methods provide plausible results in the form of high quality assignments achieving an acceptable tradeoff between the two decision objectives. However, a disadvantage of the AHP approach is that it is inflexible in the sense that a large portion of its pre-assessments have to be reiterated if the set of weapon systems and/or threats is adapted or updated. A bi-objective additive utility function solution approach to the weapon assignment problem is also developed as a result of various assessments having been carried out in conjunction with a military expert. The assignment of weapon systems to threats is again achieved by means of a greedy assignment heuristic and a utility assignment model. Both these methods again provide high quality assignments of weapon systems to threats, achieving an acceptable trade-off between the two decision objectives. However, a disadvantage of the utility function approach is that if additional weapon systems are added to the current set of weapon systems, which achieve objective function values outside the current ranges of the values employed, new utility functions have to be determined for the relevant objective function. Moreover, both the AHP and utility function approaches are also constrained by generating only one solution at a time. A final solution approach considered is the implementation of a multiobjective evolutionary metaheuristic, known as the Nondominated Sorting Genetic Algorithm II (NSGA II). This approach provides very promising results with respect to high quality assignments of weapon systems to threats. It is also flexible in the sense that additional weapon systems and threats may be added to the current sets without the need of considerable additional computations or significant model changes. A further advantage of this approach is that it is able to provide an entire front of approximately pareto optimal solutions to the fire control officer. / AFRIKAANSE OPSOMMING: In ’n militêre grond-gebaseerde lugafweeromgewing vereis bates op die grond beskerming teen vyandelike vliegtuie wat die beskermde lugruim binnedring. Hierdie vliegtuie word deur middel van ’n netwerk van sensors waargeneem en deur middel van ’n ontplooing van ’n verskeidenheid grond-gebaseerde wapenstelsels afgeweer. ’n Afvuur-beheer operateur is verantwoordelik vir die besluit om wapenstelsels aan vliegtuie wat as bedreigings geklassifiseer is, toe te wys. Die onderliggende probleem is dus om die beste stel wapens, volgens ’n voorafbepaalde kriterium of ’n stel kriteria, aan die bedreigings toe te wys. Hierdie probleem staan as die wapentoewysingsprobleem bekend. Die toestande waaronder die afvuur-beheer operateur besluite ten opsigte van wapentoewysings maak, is besonder stresvol. ’n Gebrek aan tyd is ’n uiters beperkende faktor, en die afvuurbeheer operateur moet gevolglik binne ’n tydspan wat weinige analise en geen ruimte vir foute toelaat, wapentoewysings volgens sy beperkte kennis en intuïsie maak. ’n Gerekenariseerde bedreigingsafskatting-en-wapentoekenningstelsel kan gebruik word om die operateur met besluitsteun te bedien. In sò ’n besluitsteunstelsel is ’n bedreigingsafskattingdeelstelsel verantwoordelik om vliegtuie wat die beskermde lugruim binnedring as bedreigings of andersins te klassifiseer en ten opsigte van eliminasie te prioritiseer, terwyl ’n wapentoewyingsdeelstelsel verantwoordelik is om wapentoewysings aan die bedreigings voor te stel. Die hoofdoel in hierdie tesis is om die wapentoewysingsprobleem as ’n multikriteria-besluitnemingsprobleem te modelleer. ’n Lys van relevante doelwitte is met behulp van ’n wapentoewysingsvraelys verkry wat aan militêre kenners vir voltooing uitgestuur is. Twee van hierdie doelwitte, naamlik toewysingskoste en geakkumuleerde enkelskoot-trefwaarskynlikheid, is vir illustratiewe doeleindes gebruik om ’n twee-doelwit wapentoewysingsprobleem te formuleer wat met behulp van drie multikriteria-besluitnemingsmetodologië uit die literatuur in die konteks van ’n realistiese, gesimuleerde grond-gebaseerde lugafweerscenario opgelos word. Die analitiese hiërargiese proses (AHP) is met behulp van assesserings in samewerking met ’n militêre kenner geïmplementeer. Die toewysing van wapenstelsels is met behulp van ’n gulsige toewysingsheuristiek asook aan die hand van ’n AHP-toewysingsmodel bepaal. Beide hierdie metodes is in staat om resultate van hoë gehalte te behaal wat ’n aanvaarbare afruiling tussen die twee doelwitte verteenwoordig. ’n Nadeel van die AHP is egter dat dit onbuigsaam is in die sin dat ’n groot hoeveelheid vooraf-assesserings herhaal moet word indien meer wapenstelsels en/of bedreigings by die huidige sisteem gevoeg word. ’n Twee-doelwit additiewe nutsfunksiebenadering tot die wapentoewysingsprobleem is ook met behulp van velerlei assesserings in samewerking met ’n militêre kenner ontwikkel. Die toewysings is weereens met behulp van ’n gulsige wapentoewysingsheuristiek asook ’n nutstoewysingsmodel bepaal. Beide hierdie metodes is ook in staat om resultate van hoë gehalte te behaal wat ’n aanvaarbare afruiling tussen die twee doelwitte verteenwoordig. ’n Nadeel van die nutsfunksiebenadering is egter dat indien addisionele wapenstelsels by die huidige stel wapenstelsels gevoeg word, en indien die waardes van hierdie addisionele wapenstelsels buite die grense van die doelfunksiewaardes van die huidige wapenstelsels val, daar ’n nuwe nutsfunksie vir die relevante doelwit van voor af bereken moet word. Beide die AHP- en die nutsfunksiebenaderings is verder tot die lewering van slegs een oplossing op ’n slag beperk. Laastens is ’n multikriteria evolusionêre metaheuristiek (die NSGA II) geïmplementeer wat ook goeie resultate in terme van hoë-gehalte toewysings van wapenstelsels aan bedreigings lewer. Die voordeel van hierdie benadering is dat dit buigsaam is in die sin dat die getal wapenstelsels en bedreigings in die huidige sisteem aangepas kan word sonder om noemenswaardig meer berekeninge of groot modelveranderinge teweeg te bring. ’n Verdere voordeel is dat die metaheuristiese benadering daartoe in staat is om ’n front van benaderde pareto-optimale oplossings gelyktydig te lewer.

Orientador: José Roberto Sanches Mantovani / Resumo: Neste trabalho é proposto o desenvolvimento de uma ferramenta computacional para o planeja-mento e despacho ótimo de fontes de potência ativa, considerando as incertezas das cargas (le-ve, nominal e pesada) e fontes de energia renováveis não despacháveis através de uma aborda-gem probabilística. O modelo matemático é um problema de programação não linear inteiro misto, multiobjetivo, não convexo e probabilístico na sua forma original sem a necessidade de realizar qualquer tipo de simplificação ou linearização tanto das funções objetivo como das res-trições. Um algoritmo baseado na meta-heurística Non-dominated Sorting Genetic Algorithm (NSGA-II) é proposto para resolver o problema de maneira eficaz. Os resultados obtidos com as simulações realizadas usando a implementação computacional nos sistemas de testes IEEE30 barras e IEEE118 barras mostram a eficiência e robustez da metodologia proposta. / Abstract: This work proposes the development of a computational tool for the planning and optimal dispatch of active power sources, considering the uncertainties of the loads (light, nominal and heavy) and non-dispatchable renewable energy sources through a probabilistic approach. The mathematical model is a multi-objective mixed-integer nonlinear programing problem, that is nonconvex and probabilistic in its original form, without the need to perform any kind of simplification or linearization of both objective functions and constraints. An algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) meta-heuristic is pro-posed to solve the problem effectively. The results obtained with the simulations performed using the computational implementation in the IEEE30 bus and IEEE118 bus test systems show the efficiency and robustness of the proposed methodology. / Doutor

A growing interest in distributed systems of small satellites has recently emerged due to their ability to perform a variety of new mission types, increasing technical capability, and reduced time and cost for development. However, the lack of available and dedicated small launch services currently restricts the establishment of these systems in orbit. Secondary payload launch opportunities and alternative deployment strategies can address the issue of access-to-orbit and support the delivery of the constellation to the correct orbit configuration following launch. Of these deployment strategies, the method of indirect plane separation, which utilises the natural precession of Earth orbits, is particularly applicable to the deployment of small satellite constellations due to the potential to significantly reduce propulsive requirements, albeit at the cost of increased deployment time. A review of satellite constellation design revealed that existing methods and tools are not suitable for the analysis of small satellite constellations and are not equipped to investigate alternative deployment strategies, despite the potential benefits of improved access-to-orbit, reduced system complexity, and reduced cost. To address the identified gaps in the design process, a methodology in which the analysis of small satellite constellation deployment is integrated into the system design framework is presented in this thesis. The corresponding system design-space is subsequently explored using a numerical optimisation method, which aids the identification of effective system designs and promotes the understanding of relationships between the design variables and output objectives. The primary objectives of this methodology are to ensure that the different opportunities for deployment of small satellite constellations are thoroughly examined during the design process and to support the development of improved mission and system designs. The presented methodology is demonstrated using a reduced order framework comprised of an analysis for the deployment of small satellite constellations, preliminary vehicle and propulsion system sizing processes, and system cost estimating relationships. Using this simplified mission design framework, the design space-exploration of three small satellite constellation mission case-studies is performed by application of a multiobjective genetic algorithm. Objectives of time-to-deploy, system mass, and system cost are used to direct the optimisation process and search for the most effective solutions in the system design-space. In order to perform the analysis of constellation deployment by the process of indirect plane separation, a simulation method using a semi-analytical propagation technique and time-varying atmospheric density model was developed and verified by comparison to the actual deployment of the FORMOSAT-3/COSMIC mission. The results of the case-studies presented illustrate the ability of the developed methodology to support the design process for satellite constellations and enable the identification of promising and improved system architectures for further development. Moreover, through the enumeration and quantification of the system design-space and tradespace, the methodology is shown to support the identification of relationships and trends between the design variables and selected output objectives, increasing the knowledge available to the system design team during the design process.

Diante dos desafios impostos pelo sistema econômico, características dos mercados e exigências dos clientes, as empresas são forçadas a operar com lotes de produção cada vez menores, dificultando a gestão de operações e a otimização dos sistemas produtivos. Desse modo, intensifica-se nos meios corporativos e acadêmicos a busca por abordagens que possibilitem a criação de diferenciais competitivos de mercado, sendo esta a justificativa prática deste trabalho, que propõe uma sistemática integrada para alocação, sequenciamento e balanceamento de lotes em um horizonte de programação em múltiplas linhas de produção em um sistema multiproduto com operadores polivalentes. A sistemática proposta foi dividida em três fases. A primeira fase utiliza um algoritmo genético multiobjetivo com o intuito de determinar a linha de produção em que cada lote será produzido. A segunda fase é responsável pelo sequenciamento dos lotes produtivos e se apoia em uma alteração da regra Apparent Tardiness Cost (ATC). Na terceira fase utilizou-se o método Ranked Positional Weight (RPW) para balancear a distribuição das tarefas entre os operadores polivalentes de cada linha de produção, respeitando a precedência das tarefas. A sistemática foi aplicada em dados reais do segmento têxtil, aprimorando os indicadores produtivos e de entrega e conferindo maior flexibilidade ao processo frente à demanda sazonal. / Faced with the challenges imposed by the economic system, characteristic of the markets and requirements of the customers, the companies are forced to operate with smaller production batches, making it difficult to manage operations and optimization of the production systems. In this way, the search for improvements that allow the creation of competitive differentials of market is intensified in the corporate and academic circles. This is the practical justification for this work, which proposes an integrated systematics for the allocation, sequencing and balancing of batches in a horizon of programming in multiple production lines in a multiproduct system with multipurpose operators. The systematic proposal was divided into three phases. The first phase uses a multiobjective genetic algorithm with intention to determine the production line in which each batch will be produced. The second phase is responsible for the sequencing of productive batches and is based on a change in the rule Apparent Tardiness Cost (ATC). In the third phase the method Ranked Positional Weight (RPW) was used to balance the distribution of the tasks between the multipurpose operators of each line of production, respecting the precedence of the tasks. The systematics was applied in real data of the textile segment, improving the productive and delivery indicators and giving greater flexibility of the process against the seasonal demand.

Notre travail de recherche traite la problématique de la conception d’une chaîne logistique multi-niveaux tout en tenant compte du cycle de vie du produit. Par cycle de vie du produit, nous voulons dire la succession des quatre phases de commercialisation que traverse un produit à travers le temps, à savoir : l’introduction, la croissance, la maturité et le déclin. L’objectif est de mette en place un modèle mathématique qui soit fondé sur une analyse approfondie des différents acteurs de la chaîne, selon la phase du cycle de vie du produit.Trois principaux modèles ont été développés dans cette thèse. Chacun fait l’objet d’un chapitre à part entière.Le premier modèle développé vise à concevoir une chaîne logistique de coût minimum, tout en prenant en considération l’efficacité des différents acteurs potentiels calculée selon plusieurs critères (coût, qualité, innovation, qualité du service, délais de livraisons, …), ainsi que sa variation au cours du cycle de vie du produit. Un deuxième modèle a été mis en place pour la conception d’une chaîne logistique durable, tout en prenant en considération le cycle de vie du produit. Dans ce modèle, trois objectifs différents ont été pris en compte à la fois, à savoir, un objectif économique, un objectif environnemental et un objectif social. Dans les deux premiers modèles, nous avons supposé que le produit aura un cycle de vie classique. Cependant, dans la réalité, ceci n’est pas toujours le cas. En effet, quelques produits connaissent des cycles de vie très atypiques et donc très éloignés de la courbe d’un cycle de vie théorique. Pour ce faire, un troisième modèle stochastique a été proposé pour la conception d’une chaîne logistique robuste, tenant compte des différents scénarios du cycle de vie du produit. / Our research addresses the problem of designing a multi-level supply chain, while taking into consideration the product life cycle. By product life cycle, we mean the succession of the four marketing stages that a product goes through since its introduction to the market and until it will be removed from. All products have a life cycle which can be classified into four discrete stages: introduction, growth, maturity and decline.Depending on the product life cycle phases, and based on a thorough analysis of the different supply chain potential actors, this study aims to establish mathematical models to design an efficient supply chain network. Three main models have been developed in this thesis. The first proposed model aims to design a product-driven supply chain with a minimal total cost, taking into consideration the evaluation of the different potential actors effectiveness, according to several criteria (cost, quality, innovation, quality service, timely delivery, ...).A second model was developed to design of a sustainable supply chain network, taking into account the product life cycle. In this model, three different objectives at the time were considered, namely, an economic objective, an environmental objective and a social objective.In the two previous models, we have assumed that the product has a classical life cycle. However, in the reality this is not always the case. Indeed, some products have very atypical life cycles, whose curves are very different from the classical one. To tackle this problem, in the third part of this thesis, we propose a stochastic model to design a robust supply chain network, taking into account the different product life cycle scenarios.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-10-02T15:03:23Z No. of bitstreams: 1 ALLAN SARMENTO VIEIRA - TESE PPGRN) 2011.pdf: 3588977 bytes, checksum: 796c34c01f0797a7b020aa902fa99eeb (MD5) / Made available in DSpace on 2018-10-02T15:03:23Z (GMT). No. of bitstreams: 1 ALLAN SARMENTO VIEIRA - TESE PPGRN) 2011.pdf: 3588977 bytes, checksum: 796c34c01f0797a7b020aa902fa99eeb (MD5) Previous issue date: 2011-08-12 / Capes / A utilização de modelos matemáticos na análise de sistemas de recursos hídricos é bastante discutida na literatura, entretanto todos apresentam simplificações quanto a representação matemática da dinâmica dos seus processos ou nas aproximações numéricas das equações não-lineares que descrevem o seu comportamento. Dependendo da aplicabilidade, tais simplificações podem comprometer uma tomada de decisão. Em geral, os modelos de simulação disponíveis para planejamento de sistemas de recursos hídricos a nível de bacia hidrográfica, apesar de serem bastante versáteis, não conseguem considerar certas complexidades devido a algumas limitações matemáticas dos seus algoritmos. Neste contexto foi proposto um modelo de simulação para esta finalidade, que tem como principais características o desenvolvimento de um modelo quali-quantitativo integrado com os múltiplos usos de águas superficiais, a incorporação de não-linearidades dos processos hidráulicos e operacionais e uma função multiobjetivo que otimize, segundo critérios de prioridade, o atendimento das demandas quantitativas hídricas dos diferentes usos e qualitativas relativas ao atendimento de metas de enquadramento para uso, segundo as normas do CONAMA, assim como o atendimento de outras metas operacionais. Os parâmetros de qualidade da água envolvidos são: Demanda Bioquímica de Oxigênio, Oxigênio Dissolvido, Fósforo Total, Nitrogênio Total, Clorofila-a e Coliformes Fecais. As limitações operacionais e hidráulicas foram incluídas no modelo através de restrições lineares (balanço hídrico nos nós, volumes metas, volumes mínimos, capacidade dos componentes, etc.) e não-lineares (vazão vertida máxima, vazão descarregada máxima, área da superfície líquida do reservatório, etc.). As restrições não-lineares foram tratadas a partir de aproximações por segmentos lineares (artifícios de linearização) e resolvidas num processo iterativo (programação linear sequencial) até a convergência do processo a uma tolerância desejada para o erro relativo da função objetivo. As equações do balanço de massa para os parâmetros de qualidade da água, que geralmente requerem o produto de variáveis de decisão, foram linearizadas pelo Método das Aproximações Lineares e agregadas, num mesmo algoritmo, às equações do balanço hídrico. Para avaliar o desempenho do atendimento das demandas hídricas, foram incluídos, no modelo, alguns indicadores de análise de desempenho, como a confiabilidade, vulnerabilidade, resiliência e sustentabilidade. Sua aplicabilidade foi verificada através de uma análise sistêmica dos reservatórios Engenheiro Ávidos e São Gonçalo da bacia hidrográfica do Rio Alto Piranhas - PB e suas demandas quali-quantitativas. A análise deste sistema foi realizada através da idealização de quatro cenários de operação que envolvia o uso de prioridades diferentes e a inclusão de uma Estação de Tratamento de Esgoto - ETE no último cenário. O horizonte de tempo foi de 360 meses. Foram analisados o atendimento às demandas e o enquadramento dos níveis de concentração dos parâmetros de qualidade da água à Classe II do CONAMA 357/05. Os resultados demonstraram que todas as restrições do sistema foram satisfeitas e que as demandas quantitativas obtiveram diferentes garantias de atendimento de acordo com o cenário utilizado. A inclusão da ETE considerada no cenário 04 foi imprescindível para aumentar o atendimento aos usos da água e melhorar a qualidade da água no sistema. O modelo proposto mostrou-se eficiente, quer seja quanto ao tempo de processamento quanto ao atendimento de todas as restrições impostas ao sistema. Apresentou, também, um erro numérico relativamente baixo. / The use of mathematical models in the analysis of water resources systems has been widely discussed in the literature, although all of them present simplifications regarding or to the mathematical representation of its dynamic processes or numerical approximations of the nonlinearities that describe their behavior. Depending upon the model applicability, such simplifications may compromise a decison making. All simulation models available for riverbasin water resources system planning, although being very versatile, are not able to include certain complexities due to some mathematical limitations of their algorithms. Based on this context, to deal with these problems, a new simulation model has been proposed, which has, as main characteristics, the development of an integrated qualiquantitative multiuse surface water systems model, the inclusion of nonlinearities of hydraulic and operational processes and a multiobjective function that otimizes, according to priorities criteria, the fulfillment of water demands for the different uses and the targeted water quality levels, according to the CONAMA norms as well as of other operational targets. The considered water quality parameters were the Biochemical Oxygen Demand, the Dissolved Oxygen, the Total Phosphorus, the Total Nitrogen, the Chlorophyll-a and the Faecal Coliform. The operational and hydraulic limitations were included in the model through linear constraints (water balance, target volumes, minimum volumes, component capacities, etc.) and nonlinear ones (maximum reservoir spillage and discharge flows, reservoir surface water, etc.). The nonlinear constraints were approximated by linear segments (linearization artifices) and solved in an iterative process (sequential linear programming) until a desired tolerance for the objective function relative error was reached. The mass balance for water quality parameters, which requires a multiplication of decison variables, were linearized by the Linear Approximation Method and interacted, in the same algorithm, with the water balance equations. To evaluate the performance of the fulfillment of water demand requirements, some performance indicators, such as reliability, resilience, vulnerability and sustainability, were included in the model. The model's applicability were tested in a systemic analyis of two reservoirs, Engenheiro Avidos and São Gonçalo ones, and their water quali-quantitative demands, which are located in Alto Piranhas riverbasin, PB. The analysis of this system was accomplished through the idealization of 4 operation scenarios, which made use of different priorities and the inclusion of a Waste Water Treatment Plant (ETE) in the last scenario. The simulation time horizon was 360 months. The fulfillment of water demand requirements and of the CONAMA 375/05 Class II targeted concentration level for water quality parameters were analyzed. The results have shwon the all constraints were satisfied and the reliability of water demands requirement fulfillment were different for each of the simulated scenario. The ETE inclusion scenario helped to improve the fulfillment of water demand uses requirement and to improve the system water quality. The new model proved to be efficient regarding to the computer time requirement to achieve a solution as well as to satisfy all constraints of the system. It also presented a small numerical error.

Cette thèse suit une démarche « materials-by-design » avec pour objectif le développement d'une méthode de conception dédiée aux panneaux sandwichs architecturés pour l'obtention de propriétés multifonctionnelles. Cette méthode s'appuie sur l'utilisation d'un algorithme génétique permettant simultanément une sélection de matériaux (variables discrètes) et un pré-dimensionnement du panneau (variables continues). Trois architectures de cœur ont été étudiées : les mousses, les nids-d'abeilles hexagonaux et les treillis tétraédriques. Dans cette thèse, on définit deux approches différentes de sélection des matériaux. Dans un premier temps, les matériaux architecturés sont considérés comme des matériaux existants, dont les propriétés sont référencées dans une base de données fermée. Cette approche est appelée optimisation par « voie réelle ». Afin d'ouvrir les possibilités en termes de sélection de matériaux, la deuxième approche considère une description semi-continue des matériaux architecturés et est appelée optimisation par « voie virtuelle ». Le matériau cœur est décrit par un matériau constitutif (variable discrète) et par une ou plusieurs variables géométriques continues représentant l'architecture. Utilisant ces deux approches, différentes propriétés d'emploi des panneaux sandwichs sont évaluées : rigidité et résistance en flexion, atténuation acoustique, résistance et isolation thermique, et enfin résistance aux chocs impulsionnels. Chaque fonction est optimisée à masse minimale par optimisation bi-objectifs. Différents cas d'optimisation tri-objectifs sont également présentés afin d'évaluer la compatibilité entre propriétés. En effet, la forme de la surface de compromis obtenue donne une indication sur la compatibilité entre les différents critères. Cette étape d'optimisation permet également l'identification des paramètres de conception optimaux. Dans le cas d'une optimisation par « voie virtuelle », une comparaison directe entre architectures est aussi possible. Cependant, la démarche d'optimisation mise en place est complexe car globale et travaillant avec des variables mixtes. Deux méthodes mixtes, couplant l'algorithme génétique avec d'autres approches, sont proposées pour permettre un accroissement de la complexité de l'analyse tout en garantissant une complexité raisonnable de l'optimisation. / The present thesis aims at developing a design method dedicated to the optimization of architectured sandwich panels for multifunctional properties following a “materials-by-design” approach. This method is based on a genetic algorithm which enables to deal with materials selection (discrete variables) and geometrical dimensioning (continuous variables) simultaneously. Three core architectures have been investigated: foams, hexagonal honeycombs and tetrahedral truss structures. In this thesis, two main paths for material selection are defined. In the first one, architectured materials are considered as existing materials with properties referenced in a closed materials database. This is called the “real path” optimization. In order to expand the range of possibilities in terms of materials selection, a semi-continuous description of the architectured materials is considered in the second path, which is called “virtual path” optimization. The core material is described by a constitutive material (discrete variable) and a set of continuous geometrical variables representing the architecture. Using these two aforementioned approaches, several working properties of sandwich panels have been evaluated: flexural stiffness and strength, acoustic damping, thermal resistance and insulation, and finally blast mitigation. Bi-objective optimizations were performed in order to optimize each property in a minimal weight design. Some tri-objective cases are also presented, thus assessing the compatibility between different specifications. Indeed, this is achieved by relating trade-off surface shape to the compatibility between specifications. The optimization results also help identify the optimal design regarding the different criteria. Using the “virtual path” approach, a direct comparison between the different core architectures is achievable. Nevertheless, by being global and dealing with mixed variables, the obtained optimization process is complex. Two mixed methods where genetic algorithm is coupled with other approaches are proposed in order to increase the analysis complexity while providing a reasonable optimization complexity.

Submitted by ELAYNNE XAVIER SOUZA ARAÚJO null (elaynnearaujo@hotmail.com) on 2018-03-13T18:51:38Z No. of bitstreams: 1 Tese_Final.pdf: 5331631 bytes, checksum: 60e1011da397d7e88cc9d80319169d76 (MD5) / Approved for entry into archive by Cristina Alexandra de Godoy null (cristina@adm.feis.unesp.br) on 2018-03-14T12:06:56Z (GMT) No. of bitstreams: 1 araujo_exs_dr_ilha.pdf: 5331631 bytes, checksum: 60e1011da397d7e88cc9d80319169d76 (MD5) / Made available in DSpace on 2018-03-14T12:06:56Z (GMT). No. of bitstreams: 1 araujo_exs_dr_ilha.pdf: 5331631 bytes, checksum: 60e1011da397d7e88cc9d80319169d76 (MD5) Previous issue date: 2018-02-23 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Neste trabalho é proposto o desenvolvimento de uma ferramenta computacional para o planeja-mento e despacho ótimo de fontes de potência ativa, considerando as incertezas das cargas (le-ve, nominal e pesada) e fontes de energia renováveis não despacháveis através de uma aborda-gem probabilística. O modelo matemático é um problema de programação não linear inteiro misto, multiobjetivo, não convexo e probabilístico na sua forma original sem a necessidade de realizar qualquer tipo de simplificação ou linearização tanto das funções objetivo como das res-trições. Um algoritmo baseado na meta-heurística Non-dominated Sorting Genetic Algorithm (NSGA-II) é proposto para resolver o problema de maneira eficaz. Os resultados obtidos com as simulações realizadas usando a implementação computacional nos sistemas de testes IEEE30 barras e IEEE118 barras mostram a eficiência e robustez da metodologia proposta. / This work proposes the development of a computational tool for the planning and optimal dispatch of active power sources, considering the uncertainties of the loads (light, nominal and heavy) and non-dispatchable renewable energy sources through a probabilistic approach. The mathematical model is a multi-objective mixed-integer nonlinear programing problem, that is nonconvex and probabilistic in its original form, without the need to perform any kind of simplification or linearization of both objective functions and constraints. An algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) meta-heuristic is pro-posed to solve the problem effectively. The results obtained with the simulations performed using the computational implementation in the IEEE30 bus and IEEE118 bus test systems show the efficiency and robustness of the proposed methodology. / 167761/2014-5

Submitted by DOUGLAS MIRANDA RODRIGUES null (douglasnet@gmail.com) on 2016-10-20T13:35:28Z No. of bitstreams: 1 Dissertação - Douglas Miranda Rodrigues.pdf: 8525562 bytes, checksum: de3f28242f3d17929bb0eb8ddc912f55 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-10-26T18:00:28Z (GMT) No. of bitstreams: 1 rodrigues_dm_me_guara.pdf: 8525562 bytes, checksum: de3f28242f3d17929bb0eb8ddc912f55 (MD5) / Made available in DSpace on 2016-10-26T18:00:28Z (GMT). No. of bitstreams: 1 rodrigues_dm_me_guara.pdf: 8525562 bytes, checksum: de3f28242f3d17929bb0eb8ddc912f55 (MD5) Previous issue date: 2016-10-10 / Em diversas áreas de trabalho, da Engenharia à Economia, os problemas se apresentam como sendo multiobjetivos, característica que torna complexa a tomada de decisão. Geralmente, estes objetivos são conflitantes e faz-se necessário o uso de técnicas de otimização para a obtenção de melhores resultados. Na presente dissertação serão estudados alguns métodos para a resolução destes problemas, com o objetivo de aplicar métodos de aglutinação em problemas de projetos de experimentos com múltiplas respostas. Deste modo, inicialmente foi realizada uma análise bibliométrica sobre os diferentes métodos utilizados para a resolução destes problemas. A partir disto, foi desenvolvida uma nova abordagem, utilizando a Programação por Compromisso (Compromise Programming – CP) e a Programação por Metas (Goal Programming – GP), bem como diferentes algoritmos (Gradiente Reduzido Generalizado – GRG e a metaheurística do software Optquest) que são usualmente adotados, com comparação de resultados e análise. De modo geral, esta nova proposta apresentou resultados melhores em relação à abordagem tradicional (desirability), qualificando este procedimento como uma alternativa na otimização de múltiplas respostas. / In many areas, from Engineering to Economics, problems present themselves as multiobjective, which makes a decision-making process complex. Generally, these are conflicting objectives, and optimization techniques are necessary to achieve better results. This paper applies agglutination methods in classical problems of design of experiments with multiple responses. A bibliometric analysis was made, and a new approach was developed, using Compromise Programming – CP and Goal Programming – GP, as well as two different algorithms (Generalized Reduced Gradient – GRG and Optquest’s software metaheuristics) with results comparison and analysis. The new proposal presented better results when compared to the traditional approach (desirability), qualifying this procedure as an alternative in multiple responses optimization.