Dans cette thèse, nous nous intéressons principalement à l’étude du fonctionnement cyclique mono-produit des ateliers de traitement de surface. Notre contribution porte sur le problème d’ordonnancement associé connu dans la littérature sous le nom Cyclic Hoist Scheduling Problem (CHSP). L’objet de cette thèse est de proposer des méthodes efficaces pour la résolution des problèmes de traitement de surface dans le cas où les produits à traiter sont du même type. Nous traitons en particulier le cas où le nombre des robots présents sur la ligne est égal à deux, ce qui augmente le nombre des contraintes du problème, sachant que dans le cas mono robot, ce problème a été prouvé NP-Complet. Pour cela, nous proposons une méthode qui combine deux heuristiques et un programme linéaire mixte. Cette méthode permet notamment d’affecter les mouvements de transport à l’un des deux robots tout en gérant les risques de collision entre eux, lorsque la gamme opératoire des produits à traiter suit l’implantation des cuves.Par la suite, nous proposons une extension du modèle au cas de lignes complexes. Enfin, nous étudions le cas d’un fonctionnement mixte, pour lequel il est nécessaire de traiter dans une même installation des produits différents et des rafales de produits identiques. Dans ces conditions, la solution la plus intéressante pour les industriels est de pouvoir alterner des modes de production dynamiques et cycliques. Pour cela, nous proposons une méthode efficace permettant de résoudre le problème d’ordonnancement associé à la phase transitoire relative à ce type de fonctionnement. Elle consiste en particulier à chercher les dates d’entrée au plus tôt des produits. La principale difficulté identifiée consiste ici à passer du mode dynamique au mode cyclique, c’est-à-dire à rejoindre un cycle à partir d’une solution courante donnée, en supposant que ce cycle est connu à priori. Les méthodes élaborées dans les divers cas traités sont validées par des tests sur des benchmarks de la littérature. / In this thesis, our interest is focused on the Cyclic Hoist Scheduling Problem (CHSP) in automated electroplating lines. The aim of this study is to propose an algorithm to solve the two-hoists cyclic scheduling problem. This one consists in finding a repetitive sequence of hoists’ moves, while avoiding collision between the hoists which share a common track. The objective is to minimize the period of this repetitive cycle for single part-type production. This problem was proved to be NP-complete for lines with a single hoist. The fact that two hoists are available on the line increases the number of constraints of the problem. Then we propose a solving method combining two heuristics and a Mixed Integer Linear Program. It enables us to solve both assignment and sequencing problems, while considering spatial constraints related to hoist’moves.Subsequently, we propose an extension of the model which is adapted to complex lines. Finally, our interest is focused on solving a HSP for which it is necessary to treat in the same facility a batch of various products and a batch of identical products. Under these conditions, the most interesting solution for manufacturers is to be able to alternate the production of two batches. For this goal, we propose an efficient method to solve the scheduling problem associated. Finally, our proposed methods are validated by experimentations based on benchmarks from the literature.

Les réseaux électriques actuels connaîtront un profond changement dans les années à venir. La nouvelle génération est le Smart Grid (SG) ou le réseau électrique intelligent qui se caractérise par une couche d'information et de communication qui permet aux différents composants du réseau de communiquer. Il doit considérer tous les aspects du réseau électrique, le rendant plus intelligent et flexible. Cette notion est présentée comme une réponse à l'évolution du marché de l'électricité, visant à gérer l’augmentation de la demande tout en assurant une meilleure qualité de service et plus de sécurité.Premièrement, nous présentons une formulation de programmation linéaire mixte en entier pour optimiser les systèmes de production et de consommation d'énergie dans une maison intelligente avec un déploiement efficace de plusieurs ressources énergétiques distribuées. Ensuite, à travers la conception d'expériences avec la méthode de Taguchi, divers scénarios sont introduits en faisant varier des facteurs significatifs. Par la suite, une technique heuristique est proposée pour résoudre le problème de la gestion de l'énergie résidentielle en trouvant la solution optimale globale pendant plusieurs jours consécutifs avec une réduction significative du temps d'exécution.Deuxièmement, un modèle de gestion de l'énergie est assuré grâce à des modèles mathématiques pour optimiser l’utilisation du réseau, des ressources énergétiques renouvelables, des véhicules électriques et de la batterie, ainsi que pour différents types d'appareils thermiques et électriques. Une méthode de solution exacte est mise en œuvre pour réduire le coût de l'électricité dans une maison intelligente et pour trouver des modes de fonctionnement de différentes charges. Ensuite, un algorithme d'optimisation math-heuristique est proposé pour résoudre le problème avec un temps de simulation étendu.Enfin, nous étudions le problème de gestion de l'énergie dans un microréseau constitué de plusieurs maisons intelligentes. Chacune d'elles dépose de ressources énergétiques renouvelables, d’un véhicule électrique et d’appareils intelligents. Les ressources d'énergie renouvelable injectent l’excès de l'énergie dans un système de stockage d'énergie partagé. Un modèle mathématique linéaire mixte en entier pour la gestion d'énergie est proposé pour réduire le coût total de fonctionnement du microréseau. Des comparaisons avec des scénarios conventionnels où chaque maison intelligente possède son propre système de stockage d'énergie sont effectuées pour démontrer l’efficacité de la démarche proposée. / The current electricity grids will experience a profound change in the coming years. The new generation is the Smart Grid (SG) which is characterized by information and communication layer enabling the communication between the different components of the grid. It needs to consider all sides of power grid, making it more intelligent and flexible. This notion is presented as an answer to changes in the electricity market, aiming to manage the increased demand while ensuring a better quality of service and more safety.First, we present a mixed integer linear programming formulation to optimize the energy production and consumption systems in a smart home with an effective deployment of several distributed energy resources. Then through the design of experiments with the Taguchi method, diverse scenarios are introduced by varying significant factors. Afterward, a heuristic technique is proposed to solve the problem of residential energy management by finding the global optimum solution for many consecutive days with significant reduction of execution time.Second, an energy management model is proposed thanks to mathematical models to optimize the grid, renewable energy resources, battery and electric vehicles are presented as well as for different type of thermal and electrical appliances. An exact solution method is implemented to reduce the electricity cost in a smart home and find out operation modes of different loads. Then a math-heuristic optimization algorithm is proposed to solve the problem with extended simulation time horizon.Finally, we study a microgrid energy management problem which comprises multiple smart homes. Each of them owns renewable energy resources, one electric vehicle and smart appliances. The renewable energy resources inject the excess energy in the shared energy storage system. An optimized energy management model using mixed integer linear programming is proposed to reduce the total electricity cost in the microgrid. Comparisons with conventional scenarios where each smart home has its individual small energy storage system without sharing energy with their neighbors are done to ensure that the proposed formulation is well efficient.

Στην παρούσα διπλωματική μελέτη, σχεδιάζεται και αναπτύσσεται ένα αξιόπιστο σύστημα βαθμολόγησης και άρα αξιολόγησης των προμηθευτών απαραίτητων σε μία Εφοδιαστική Αλυσίδα Αγαθών και Υπηρεσιών. Η μεθοδολογία περιλαμβάνει: Καθορισμό Ομάδας Αξιολόγησης, Ταξινόμηση Εφοδιαστικών Απαιτήσεων (Supply Positioning) σε υλικά και υπηρεσίες (υψηλής κερδοφορίας, κρίσιμα, μη κρίσιμα, στρατηγικής σημασίας, χαμηλού κόστους & υψηλού κινδύνου), Κατάσταση Κρίσιμων Υλικών και Υπηρεσιών, Επισήμανση Δυνητικών Προμηθευτών, Προεπιλογή Προμηθευτών, Συνεργασία - Συζήτηση με Προμηθευτές, Προσδιορισμό Κριτηρίων επιλογής Προμηθευτών, Συντελεστές Βαρύτητας Κριτηρίων, Ανάπτυξη Ανάλυσης SWOT, Έρευνα για επί πλέον πληροφορίες, Σύνταξη και αποστολή Ερωτηματολογίου – Επεξεργασία, Βαθμολογία Δυνητικών Προμηθευτών, Τήρηση Αρχείου Εγκεκριμένων Προμηθευτών. Εν συνεχεία γίνεται μία επισκόπηση τεσσάρων-πέντε κύριων μεθόδων επιλογής και μία βιβλιογραφική ανασκόπηση των ερευνητικών προσπαθειών. Παρουσιάζονται αναλυτικά τα κριτήρια απόφασης, οι μέθοδοι επιλογής (εξάλειψης ή βελτιστοποίησης), τα χαρακτηριστικά του προβλήματος επιλογής προμηθευτή (στρατηγική απόφαση, συνενωτικοί κανόνες, πολλαπλοί εμπλεκόμενοι-παίκτες & διαμορφωτές λήψης απόφασης, πολλαπλά αντικειμενικά και υποκειμενικά κριτήρια, περιορισμοί τόσο των προμηθευτών όσο και της εταιρείας, και ο πιθανοκρατικός χαρακτήρας του προβλήματος) . Η προσέγγιση απαιτεί η απόφαση να ληφθεί σε δύο στάδια. Στο πρώτο στάδιο, επιλέγουμε τους στρατηγικούς προμηθευτές διαμέσου της εταιρικής στρατηγικής για να επιλεχθούν οι προμηθευτές εκείνοι που εγγυώνται την μακροπρόθεσμη βιωσιμότητα της εταιρείας και το ελάχιστο κατώφλι κάθε κριτηρίου. Στο δεύτερο στάδιο της προσέγγισης αυτής, προτείνεται ένα γραμμικό μοντέλο μικτού ακέραιου προγραμματισμού για να επιλεγούν οι καλύτεροι προμηθευτές και οι απαιτούμενες ποσότητες θεωρώντας τους περιορισμούς τόσο των προμηθευτών όσο και της επιχείρησης. Ο σκοπός αυτού του μοντέλου είναι να μεγιστοποιηθεί η συνάρτηση U που αναπαριστά τον ολικό βαθμό που δίνεται από την ομάδα απόφασης. Προτείνεται ένας τρόπος για να ληφθεί υπόψη η πιθανοκρατική συμπεριφορά των υποψήφιων προμηθευτών. Τέλος, για καλύτερη κατανόηση, παρουσιάζεται ένα αριθμητικό παράδειγμα βελτιστοποίησης α) χωρίς περιορισμούς με την προσέγγιση της μεθόδου Αναλυτικής Ιεράρχησης (AHP) και β) με περιορισμούς. Το παράδειγμα μας δείχνει ότι η μαθηματική προσέγγιση ήταν η καλύτερη μέθοδος η οποία λαμβάνει υπόψη όλους τους περιορισμούς. / In this thesis study, it is designed and developed a reliable system calibration and evaluation of suppliers so necessary in a Supply Chain of Goods and Services. The methodology includes: Evaluation Team Specification, Supply Requirements Sorting (Supply Positioning) for materials and services (high profitability, critical, non-critical, strategic, low cost & high risk), Critical Materials and Services Condition, Potential suppliers Highlight, Suppliers Pre-selection, Cooperation - Discussion with Suppliers, Vendor Selection Criteria Identification,, Criteria Weight Credits, SWOT Analysis Development, Research for additional information, Writing, Editing and sending questionnaires, Potential suppliers Review, Approved Suppliers File Records (Archives). An overview of four to five core selection methods and a literature review of research efforts are following. The decision criteria, the selection methods (optimization or elimination) and the characteristics of the supplier selection problem (strategic decision, conjunctive rules, multiple stakeholders-players & decision makers, multiple objective and subjective criteria, constraints regarding to suppliers and the company, the probabilistic nature of the problem) are presenting in details. This approach requires a decision taken in two stages. In the first stage, we select strategic suppliers through the corporate strategy in order to select those suppliers that guarantee the long term viability of the company and the minimum threshold for each criterion. In the second stage of this approach, it is proposed a mixed-integer linear programming model to select the best suppliers and the required quantities considering the limitations of suppliers and the business as well. The purpose of this model is to maximize the function U representing the overall degree given by the group decision. It is also proposed a way to take into account the probabilistic behavior of supply candidates. Finally, for better understanding, a numerical example of optimization is presented a) without restrictions with the approach of Analytic Hierarchy process (AHP) and b) with restrictions. The example shows that the mathematical approach was the best method which takes into account all the constraints.

No description available.

Le travail réalisé dans le cadre de cette thèse propose une démarche de sélection de partenaires (fournisseurs et prestataires) dans une chaîne logistique durable en boucle fermée. Il s’agit d’évaluer les partenaires en fonction de critères économiques, environnementaux, et sociétaux puis de sélectionner ceux qui interviennent dans la chaîne logistique en respectant un ensemble des contraintes. Nous développons une méthode d’évaluation et de classement des partenaires basée sur une approche hybride en utilisant les méthodes AHP et PROMETHEE, dans un environnement flou. Ensuite, nous proposons un modèle mathématique multi-objectif qui permet non seulement de minimiser le coût total de la chaîne logistique, mais également de maximiser la valeur totale de l’approvisionnement, minimiser les émissions de gaz à effet de serre et maximiser le bénéfice sociétal. Nous utilisons une approche max-min pondérée pour résoudre le modèle proposé à l’aide de l’outil de modélisation et d’optimisation GAMS. / Reverse logistics network design is a crucial issue in which it is important to take into account the selection of the most appropriate partner with sustainability concerns. This partner can be a supplier or a third-party reverse logistics provider (3PRLP). However, research works that consider reverse logistics (RL) network design, partner selection, and sustainability issues simultaneously are rather limited till now. This research work proposes an integrated sustainable approach for partner selection and closed-loop supply chain (CLSC) network configuration, particularly in the case of outsourcing reverse logistics process to third-party provider. We propose a trade-off between sustainability criteria for both supplier and 3PRL provider selection. A multi-objective mixed-integer programming (MILP) model is also proposed to configure CLSC network and to select the best partners. The model minimizes the total cost of sourcing, and the total greenhouse gas emissions, while it maximizes the total value of reverse logistics, and the number of new job opportunities. A numerical example is also presented to illustrate the proposed approach.

[pt] Esta tese de doutorado é composta de dois artigos científicos com contribuições na área de Smart Grid. Além disso, a tese também contribui para o desenvolvimento de soluções computacionais eficientes para problemas de programação linear mista e inteira. Outra importante contribuição é o desenvolvimento de método de decomposição benders com segundo estágio inteiro e não convexo aplicado ao problema de Transmission Switching. O primeiro artigo científico mostra os benefícios com o advento de uma rede inteligente e o aumento da capacidade do operador do sistema de energia elétrica em tomar ações corretivas em face de ocorrências de contingências. O artigo também analisa consequências práticas na capacidade de self-healing da rede pós-contingência. Em nosso contexto, uma rede self-healing é uma rede com total flexibilidade para ajustar a geração e as linhas de transmissão antes e depois da ocorrência de alguma contingência. Resultados numéricos mostram significantes reduções no corte de carga para cada contingência e no total. Foi considerado um único período que representa a demanda de pico do sistema, comparou-se o novo método com os utilizados em publicações anteriores. O segundo artigo contribui também para a aplicação da tecnologia de Smart Grid, em particular a teoria de Transmission Switching. De fato, desenvolvemos uma estratégia de solução para lidar com a complexibilidade NP-Hard criada pelas variáveis de transmission switching e unit commitment do problema de otimização. Foi desenvolvida uma solução algorítmica baseada na teoria dos grafos. Estudou-se a estrutura topológica desses problemas. Além disso, a maior contribuição foi o desenvolvimento de um novo método de decomposição de benders aplicado para o problema de transmission switching com o segundo estágio inteiro e não convexo. Para lidar com este problema de não convexidade, foi desenvolvido um método de convexificação sequencial, implícito a decomposição de benders. / [en] This PhD Thesis is composed by two papers with contributions on operations research applied to smart grid theory. The first paper highlights the economic and security benefits of an enhanced system operation with the advent of a smart grid technology by introducing a novel model, which is a joint energy and reserve scheduling that incorporates the network capability to switch transmission lines as a corrective action to enhance the system capability to circumvent contingency events. The main goal is to reduce operating costs and electric power outages, by adjusting the network connectivity when a contingency occurs. In such a framework, results show that, with a limited number of corrective switches, the system operator is able to circumvent a wider range of contingencies, while resulting in lower operational costs and reserve levels. In our context, a grid that is capable to adjust its generation and also its topology through post-contingency line switching is called a self-healing grid, and its importance in network security and operating costs is demonstrated in this work. The graph structure is explored in the algorithmic solution of the post-contingency transmission switching problem. Numerical results demonstrate a significant reduction in total load shedding and operating cost. It has been also illustrated an expressive improvement in terms of security and operating cost, in comparison to the transmission switching models previously published. The second paper is an application of a modified Benders decomposition to the post-contingency transmission switching problem. The decomposition is an attempt to deal with the NP-hard optimization problem created by the transmission switching and unit commitment variables. The major contribution is the application of a new benders decomposition approach to the problem of transmission switching, in which the first and second stages problems are a mixed-integer program. To deal with this issue, it is used a Branch and Bound (B&B) procedure for the first-stage problem and a sequential convexification procedure for the second-stage problem.

Dans cette thèse, nous considérons le problème du séquencement sur une ligne de montage multi-modèles de véhicules industriels. Pour équilibrer au mieux la charge dynamique des opérateurs, la minimisation de la somme des retards à l’issue de chaque véhicule est proposée.Deux approches peuvent être utilisées pour optimiser le lissage de charge dans un problème de séquencement : l’utilisation directe des temps opératoires ou le respect de règles. La plupart des travaux appliqués à l’industrie automobile utilisent l’approche de respect de règles. Une originalité de ce travail est d’utiliser l’approche de la prise en compte directe des temps opératoires.L’étude de la littérature de ce problème a dévoilé deux lacunes dans les travaux précédents : l’essentiel des travaux modélisent un seul type d’opérateurs d’une part, et proposent des heuristiques ou des métaheuristiques pour résoudre ces problèmes, d’autre part. L’originalité de ce travail est de tester des méthodes exactes pour des instances industrielles et de modéliser le fonctionnement de trois différents types d’opérateurs spécifiques au cas industriel.Deux méthodes exactes sont développées : la programmation linéaire mixte et la programmation dynamique. Une étude expérimentale des facteurs de complexité sur des instances académiques des deux modèles est développée. Les modèles sont aussi testés sur des instances du cas d’étude.Par ailleurs, le problème est traité par deux méthodes approchées : une heuristique basée sur la programmation dynamique d’une part, et des métaheuristiques (algorithme génétique, recuit simulé et un couplage des deux) d’autre part. Les deux approches sont testées sur des instances académiques et des instances du cas d’étude.Ce travail a permis d’apporter une solution intéressante d’un point de vue industriel puisqu’il prend en compte les caractéristiques de la ligne de montage (opérateurs spécifiques) et améliore significativement la qualité du séquencement en un temps de calcul raisonnable. / In this thesis, the problem of sequencing mixed model assembly lines (MMAL) is considered. Our goal is to determine the sequence of products to minimize the work overload. This problem is known as the mixed model assembly line sequencing problem with work overload minimization (MMSP-W). This work is based on an industrial case study of a truck assembly line.Two approaches can be used to minimize the work overload: the use of task operation times or the respect of sequencing rules. Most of the earlier works applied in car industry use the latter approach. The originality of this work is to employ the task operation times for the generation of the product sequence in a MMAL.The literature review has highlighted two main gaps in previous works: most of the papers consider a single type of operators, and propose heuristics or metaheuristics to solve the problem. The originality of this work is to test exact methods for industrial case instances and to model three different types of operators.Two exact methods are developed: the mixed integer linear programming and dynamic programming. The models are tested on industrial case study instances. An experimental study is developed for both approaches in order to understand the complexity factors.Moreover, the problem is treated by two approximate methods: a heuristic based on dynamic programming and metaheuristics (genetic algorithm, simulated annealing and a hybrid method based on both genetic algorithm and simulated annealing). All approaches are tested on academic instances and on real data from the industrial case study.

[pt] No seu planejamento plurianual de investimentos, as organizações do setor de Exploração e Produção (EeP) estruturam alternativas de projetos de produção de petróleo e gás natural, sujeitas a diversas restrições e a incertezas técnicas e econômicas. Como não há como assegurar que os resultados dos projetos ocorram conforme o previsto, é possível que seu retorno seja inferior ao esperado, o que, dependendo da relevância, pode provocar um efeito adverso no resultado operacional e nas condições financeiras da companhia. Nesse mérito, a dissertação apresenta e aplica um modelo de programação estocástica linear inteira mista para seleção de portfólio de projetos que permita a maximização dos resultados, com restrição de risco. A aplicação considerou dados realistas do segmento de upstream de uma empresa do setor. Para representar os cenários econômicos, optou-se pela utilização da simulação de Monte Carlo do modelo Movimento Geométrico Browniano. Com o Valor Presente Líquido como retorno e Conditional Value-at-Risk representando a medida de risco, foi possível estabelecer a fronteira eficiente do risco-retorno, com a qual o decisor pode definir uma solução de portfólio, conforme sua aversão ao risco. / [en] In their multi-annual investment planning, oil and gas companies consider alternatives of production projects, subject to a variety of constraints, and technical and economic uncertainties. Considering that it is not possible to guarantee that these projects will perform as predicted, the return can be less than expected and can lead to a significant adverse effect to the operational results and to financial conditions of a given organization. Therefore, this dissertation proposes a mixed integer linear stochastic programming model for project portfolio selection that maximizes the return with risk constraint. The application considered realistic data from the upstream segment of an oil and gas company. Monte Carlo simulation of the Geometric Brownian Motion model was considered to represent the economic scenarios. Using the Net Present Value as the function and Conditional Value-at-Risk as a risk measure, it was possible to establish the efficient frontier of risk-return, which can assist the decision-maker to define the project portfolio according to their risk aversion.

Submitted by Izabel Franco (izabel-franco@ufscar.br) on 2016-10-06T17:59:08Z No. of bitstreams: 1 DissJFSN.pdf: 5729965 bytes, checksum: 946688f479f7780db197fa49b4b4c853 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-20T13:51:08Z (GMT) No. of bitstreams: 1 DissJFSN.pdf: 5729965 bytes, checksum: 946688f479f7780db197fa49b4b4c853 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-20T13:51:14Z (GMT) No. of bitstreams: 1 DissJFSN.pdf: 5729965 bytes, checksum: 946688f479f7780db197fa49b4b4c853 (MD5) / Made available in DSpace on 2016-10-20T13:51:20Z (GMT). No. of bitstreams: 1 DissJFSN.pdf: 5729965 bytes, checksum: 946688f479f7780db197fa49b4b4c853 (MD5) Previous issue date: 2016-03-21 / Não recebi financiamento / Vehicle routing problems occur in many practical situations where the pickup and/or delivery of goods is required. In this context, the present research aims to contribute to the study of logistic operations that arise in companies that deliver products on a regular basis to customers in densely populated urban areas. The problem consists in designing minimal cost daily routes serving the maximal number of customers. To this end, the crew of each vehicle comprise multiple deliverymen as means to reduce service times. Based on a case study in a drinks producer and distributor in the state of São Paulo, it is proposed a mixed integer linear programming model that comprise costs with own and chartered vehicles and the number of deliverymen, and various operational constraints such as time windows in customers, multiple daily trips, time limitations for the circulation of some vehicle types in specific areas, compatibility between vehicles and customers, maximum load in each vehicle, maximum route time and minimum load for the realization of a second trip. Results obtained by solving the model with real instances through exact (branch&cut), heuristic (constructive, local search, GRASP and Simulated Annealing) and hybrid (GRASP and branch&cut) approaches demonstrate the good quality of the generated solutions, and indicate the potential of application of some of these methods in practice. / Problemas de roteamento de veículos ocorrem em diversas situações práticas onde se faz necessária a distribuição e/ou coleta de produtos. Nesse contexto, a presente pesquisa visa o estudo das operações logísticas presentes em empresas que entregam produtos em base regular a clientes localizados em áreas urbanas de alta densidade demográfica. O problema consiste na obtenção de rotas de mínimo custo visando o atendimento do maior número de clientes da carteira diária. Para tal, a tripulação de cada veículo pode contemplar múltiplos entregadores para redução dos tempos de serviço. Com base em um estudo de caso em uma distribuidora de bebidas do interior do Estado de São Paulo, é proposto um modelo de programação linear inteira mista que considera custos com frota própria e fretada e com o número de entregadores, e diversas restrições operacionais, tais como janelas de tempo em clientes, múltiplas viagens diárias, limitações de horários de circulação de tipos de veículos, compatibilidade entre veículos e clientes, capacidade máxima de carga a ser transportada em cada veículo, tempo máximo de rota e carga mínima para realização da segunda viagem. Resultados da resolução do modelo para instâncias reais por meio de abordagens exatas (branch&cut), heurísticas (construtiva, busca local, GRASP e Simulated Annealing) e híbrida (GRASP e branch&cut), demonstram a boa qualidade das soluções geradas, e evidenciam o potencial de uso dessas metodologias na prática.

Made available in DSpace on 2016-06-02T19:51:48Z (GMT). No. of bitstreams: 1 3491.pdf: 1251165 bytes, checksum: 650dd47d0fec8bae05ba378f445f91dc (MD5) Previous issue date: 2011-02-11 / Universidade Federal de Sao Carlos / The aim of this work was to develop and apply a mathematical optimization model to support some key decisions in the steam production operation system with multiple industrial boilers. In the food industry, key decisions into this system are, normally, taken based on people experience, not through decision support tools based on operations research. The proposed model approaches the fuel replenishment decisions, fuel transportation and fuel inventory management. The model also determines the start-up and shutdown moments for each boiler, as well as, which of them will produce steam. An algebraic modeling language was used to implement computationally the model, which was solved by an optimization software. The adjustments and model validation were performed through a case study carried out in a large scale food industry localized in Goiania (GO). In computational experiments conducted with company s data, the results obtained by the model showed better economic performance than those from the company. In face of the good outcomes obtained by applying the model and the lack of protocols or decision tools for the studied system, this model presents itself as a feasible alternative to be considered to support some key-decisions in the steam production system with industrial boilers. / O objetivo deste trabalho foi desenvolver e aplicar um modelo matemático de otimização para apoiar algumas das principais decisões na operação de produção de vapor em múltiplas caldeiras industriais. Em indústrias de alimentos, essas decisões, em geral, são tomadas com base na experiência dos envolvidos e não com ferramentas de auxílio à tomada de decisão apoiadas pela pesquisa operacional. O modelo proposto contempla as decisões de aquisições de combustíveis dos fornecedores, o transporte para fábrica e o gerenciamento dos estoques dos combustíveis adquiridos no sistema. O modelo também determina os momentos de acionamento e desligamento das caldeiras, bem como em quais delas haverá produção de vapor. Uma linguagem de modelagem algébrica foi utilizada para implementar computacionalmente o modelo, que foi resolvido por meio de um software de otimização. Os ajustes e a validação do modelo ocorreram por meio de um estudo de caso realizado em uma indústria de alimentos de grande porte localizada em Goiânia (GO). Nos experimentos realizados com os dados fornecidos pela empresa, os resultados obtidos com o modelo apresentaram melhores desempenhos econômicos do que aqueles praticados pela operação real. Diante dos bons resultados alcançados na aplicação do modelo em situações reais e da ausência de protocolos ou ferramentas para apoiar as decisões no sistema estudado, o modelo proposto apresenta-se como uma alternativa viável para apoiar algumas das principais decisões na operação de produção de vapor em caldeiras industriais.