O objetivo de estudo desta dissertação é o desenvolvimento de um modelo de planejamento agregado da produção que apóie as decisões de nível gerencial e de diretoria das usinas de açúcar e álcool no que tange às variedades de cana colhidas em cada semana, às compras de cana-de-açúcar de terceiros, ao tipo de transporte (próprio ou terceirizado) a se utilizar em cada semana, ao total de cana moída por semana para atendimento da demanda e aos processos (industrial e comercial) que se devem escolher para produzir e comercializar açúcar e álcool. As decisões devem ocorrer em função de preços nos mercados interno, externo e mercado futuro, do fluxo de caixa da empresa, da capacidade da usina para armazenar açúcar e álcool e da possibilidade de uso de estoque de terceiros. As decisões por compra de cana, escolha de processos e venda de produtos são tomadas semanalmente num horizonte móvel de planejamento de 52 semanas, que inclui o tempo de safra no centro-sul do Brasil (meados de março a meados de dezembro, aproximadamente 36 semanas) mais o período de entressafra (aproximadamente 16 semanas, de meados de dezembro a meados de março). A procura por melhores estratégias de comercialização de tal forma a auxiliar a tomada de decisões é uma necessidade constante dos empresários do setor, que muitas vezes são surpreendidos pelas variações de preços de açúcar e álcool no mercado interno, externo e mercado futuro. Na parte comercial, este trabalho utiliza o método Delphi de previsão de preços de açúcar e álcool que balizam as tomadas de decisão no planejamento e controle da produção das usinas de açúcar e álcool. Define-se Hedge como a operação financeira de proteger determinado ativo de uma empresa contra variações inesperadas de preços. Neste trabalho, utiliza-se um modelo de escolha de mix de produto para Hedge vinculado à lucratividade e minimização de risco denominado Modelo de Semi- Variância com análise de cenários de Markowitz. Nas decisões relacionadas com as partes agrícola, industrial e comercial, faz-se uso de um modelo de programação linear inteira mista e para resolvê-lo utiliza-se o software de programação matemática LINGO e suas interfaces com a planilha eletrônica Excel. Nas decisões vinculadas ao mix ótimo para o Hedge em cada semana, faz-se uso de um modelo de programação quadrática resolvido pelo LINGO e suas interfaces com a planilha eletrônica Excel. Um estudo de caso foi realizado numa usina de açúcar e álcool no município de Junqueirópolis (SP) para validar o modelo proposto. / The objective of study this dissertation is to develop a model of aggregate production planning to support the decisions of management and board level of sugar and alcohol plants in regard to varieties of cane harvested each week, purchasing cane of nonsugar, the type of transport (own or outsourced) to use each week, the total cane processed per week for taking care of the demand and processes (industrial and commercial) and that must be chosen to produce and sell sugar and alcohol. Decisions must occur in terms of domestic, foreign and future market prices, the company\'s cash flow and the capacity to store sugar and alcohol and the possibility of using stock to third parties. Decisions about buying cane, choice of processes and products for sale are made in a weekly mobile planning horizon of 52 weeks, which includes the time of harvest in central-southern Brazil (mid-March to mid-December, approximately 36 weeks) plus the off-season (approximately 16 weeks, from mid-December to mid March). The demand for better marketing strategies to help such decision making is a constant need for entrepreneurs in the sector, which are often surprised by the changes in prices of sugar and alcohol in the internal, external and future market. In the commercial part, this study uses the Delphi method of forecasting the price of sugar and alcohol that guides the decision-making in planning and controlling the production of sugar and alcohol plants. Hedging is defined as a financial transaction to protect certain assets of a business against unexpected changes in prices. In this work, it is used a model of choice of product mix for Hedge linked to profitability and minimizing risk named Model of Semi-Variance analysis with scenarios of Markowitz. In decisions related to the agricultural, industrial and commercial parts it is used a type of mixed integer linear programming and to solve it is used the mathematical programming software LINGO and its interface with Excel spreadsheets. In decisions related to the optimal mix for Hedge in each week, is used a quadratic programming model solved by LINGO and its interface with Excel spreadsheets. A case study was conducted in a sugar mill and alcohol in the city of Junqueirópolis (SP) to validate the proposed model.

Modern manufacturing systems need new types of scheduling methods. While traditional scheduling methods are primarily concerned with sequencing of jobs, modern manufacturing environments provide the additional possibility to process jobs in batches. This adds to the complexity of scheduling. There are two types of batching namely: (i) serial batching (jobs may be batched if they share the same setup on a machine and one job is processed at a time. The machine which processes jobs in this manner is called as discrete processor) and (ii) parallel batching (several jobs can be processed simultaneously on a machine at a time. The machine which processes jobs in this manner is called as batch processor or batch processing machine). Parallel batching environments have attracted wide attention of the researchers working in the field of scheduling. Particularly, taking inspiration from studies of scheduling batch processors in semiconductor manufacturing [Mathirajan and Sivakumar (2006b) and Venkataramana (2006)] and in steel casting industries [Krishnaswamy et al. (1998), Shekar (1998) and Mathirajan (2002)] in the Management Studies Department of Indian Institute of Science, this thesis addresses a special problem on scheduling batch processor, observed in the steel casting manufacturing. A fundamental feature of the steel casting industry is its extreme flexibility, enabling castings to be produced with almost unlimited freedom in design over an extremely wide range of sizes, quantities and materials suited to practically every environment and application. Furthermore, the steel casting industry is capital intensive and highly competitive. From the viewpoint of throughput and utilization of the important and costly resources in the foundry manufacturing, it was felt that the process-controlled furnace operations for the melting and pouring operations as well as the heat-treatment furnace operations are critical for meeting the overall production schedules. The two furnace operations are batch processes that have distinctive constraints on job-mixes in addition to the usual capacity and technical constraints associated with any industrial processes. The benefits of effective scheduling of these batch processes include higher machine utilization, lower work-in-process (WIP) inventory, shorter cycle time and greater customer satisfaction [Pinedo (1995)]. Very few studies address the production planning and scheduling models for a steel foundry, considering the melting furnace of the pre-casting stage as the core foundry operation [Voorhis et al. (2001), Krishnaswamy et al. (1998) and Shekar (1998)]. Even though the melting and pouring operations may be considered as the core of foundry operations and their scheduling is of central importance, the scheduling of heat-treatment furnaces is also of considerable importance. This is because the processing time required at the heat treatment furnace is often longer compared to other operations in the steel-casting foundry and therefore considerably affects the scheduling, overall flow time and WIP inventory. Further, the heat-treatment operation is critical because it determines the final properties that enable components to perform under demanding service conditions such as large mechanical load, high temperature and anti-corrosive processing. It is also important to note that the heat-treatment operation is the only predominantly long process in the entire steel casting manufacturing process, taking up a large part of total processing time (taking up to a few days as against other processes that typically take only a few hours). Because of these, the heat-treatment operation is a major bottleneck operation in the entire steel casting process. The jobs in the WIP inventory in front of heat-treatment furnace vary widely in sizes (few grams to a ton) and dimensions (from 10 mm to 2000 mm). Furthermore, castings are primarily classified into a number of job families based on the alloy type, such as low alloy castings and high alloy castings. These job families are incompatible as the temperature requirement for low alloy and high alloy vary for similar type of heat-treatment operation required. These job families are further classified into various sub-families based on the type of heat treatment operations they undergo. These sub-families are also incompatible as each of these sub-families requires a different combination of heat-treatment operation. The widely varying job sizes, job dimensions and multiple incompatible job family characteristic introduce a high degree of complexity into scheduling heat-treatment furnace. Scheduling of heat-treatment furnace with multiple incompatible job families can have profound effect on the overall production rate as the processing time at heat-treatment operation is very much longer. Considering the complexity of the process and time consumed by the heat treatment operation, it is imperative that efficient scheduling of this operation is required in order to maximize throughput and to enhance productivity of the entire steel casting manufacturing process. This is of importance to the firm. The concerns of the management in increasing the throughput of the bottleneck machine, thereby increasing productivity, motivated us to adopt the scheduling objective of makespan. In a recent observation of heat-treatment operations in a couple of steel casting industries and the research studies reported in the literature, we noticed that the real-life problem of dynamic scheduling of heat-treatment furnace with multiple incompatible job families, non-identical job sizes, non-identical job dimensions, non-agreeable release times and due dates to maximize the throughput, higher utilization and minimize the work-in-process inventory is not at all addressed. However, there are very few studies [Mathirajan et al. (2001, 2002, 2004a, 2007)] which have addressed the problem of scheduling of heat-treatment furnace with incompatible job families and non-identical job sizes to maximize the utilization of the furnace. Due to the difference between the real-life situation on dynamic scheduling of heat-treatment furnace of the steel casting manufacturing and the research reported on the same problem, we identified three new class of batch processor problems, which are applicable to a real-life situation based on the type of heat-treatment operation(s) being carried out and the type of steel casting industry (small, medium and large scale steel casting industry) and this thesis addresses these new class of research problems on scheduling of batch processor. The first part of the thesis addresses our new Research Problem (called Research Problem 1) of minimizing makespan (Cmax) on a batch processor (BP) with single job family (SJF), non-identical job sizes (NIJS), and non-identical job dimensions (NIJD). This problem is of interest to small scale steel casting industries performing only one type of heat treatment operation such as surface hardening. Generally, there would be only a few steel casting industries which offer such type of special heat-treatment operation and thus the customer is willing to accept delay in the completion of his orders. So, the due date issues are not important for these types of industries. We formulate the problem as Mixed Integer Linear Programming (MILP) model and validate the proposed MILP model through a numerical example. In order to understand the computational intractability issue, we carry out a small computational experiment. The results of this experiment indicate that the computational time required, as a function of problem size, for solving the MILP model is non-deterministic and non-polynomial. Due to the computational intractability of the proposed MILP model, we propose five variants of a greedy heuristic algorithm and a genetic algorithm for addressing the Research Problem 1. We carry out computational experiments to obtain the performance of heuristic algorithms based on two perspectives: (i) comparison with optimal solution on small scale instances and (ii) comparison with lower bound for large scale instances. We choose five important problem parameters for the computational experiment and propose a suitable experimental design to generate pseudo problem instances. As there is no lower bound (LB) procedure for the Research Problem1, in this thesis, we develop an LB procedure that provides LB on makespan by considering both NIJS and NIJD characteristics together. Before using the proposed LB procedure for evaluating heuristic algorithms, we conduct a computational experiment to obtain the quality of the LB on makespan in comparison with optimal makespan on number of small scale instances. The results of this experiment indicate that the proposed LB procedure is efficient and could be used to obtain LB on makespan for any large scale problem. In the first perspective of the evaluation of the performance of the heuristic algorithms proposed for Research Problem 1, the proposed heuristic algorithms are run through small scale problem instances and we record the makespan values. We solve the MILP model to obtain optimal solutions for these small scale instances. For comparing the proposed heuristic algorithms we use the performance measures: (a) number of times the proposed heuristic algorithm solution equal to optimal solution and (b) average loss with respect to optimal solution in percentage. In the second perspective of the evaluation of the performance of the heuristic algorithms, the proposed heuristic algorithms are run through large scale problem instances and we record the makespan values. The LB procedure is also run through these problem instances to obtain LB on makespan. For comparing the performance of heuristic algorithms with respect to LB on makespan, we use the performance measures: (a) number of times the proposed heuristic algorithm solution equal to LB on makespan (b) average loss with respect to LB on makespan in percentage, (c) average relative percentage deviation and (d) maximum relative percentage deviation. We extend the Research Problem 1 by including additional job characteristics: job arrival time to WIP inventory area of heat-treatment furnace, due date and additional constraint on non-agreeable release time and due date (NARD). Due date considerations and the constraint on non-agreeable release times and due date (called Research Problem 2) are imperative to small scale steel casting foundries performing traditional but only one type of heat treatment operation such as annealing where due date compliance is important as many steel casting industries offer such type of heat treatment operations. The mathematical model, LB procedure, greedy heuristic algorithm and genetic algorithm proposed for Research Problem 1, including the computational experiments, are appropriately modified and\or extended for addressing Research Problem 2. Finally, we extend the Research Problem 2 is by including an additional real life dimension: multiple incompatible job families (MIJF). This new Research Problem (called Research Problem 3) is more relevant to medium and large scale steel casting foundries performing more than one type of heat treatment operations such as homogenizing and tempering, normalizing and tempering. The solution methodologies, the LB procedure and the computational experiments proposed for Research Problem 2 are further modified and enriched to address the Research Problem 3. From the detailed computational experiments conducted for each of the research problems defined in this study, we observe that: (a) the problem parameters considered in this study have influence on the performance of the heuristic algorithms, (b) the proposed LB procedure is found to be efficient, (c) the proposed genetic algorithm outperforms among the proposed heuristic algorithms (but the computational time required for genetic algorithm increases as problem size keeps increasing), and (d) in case the decision maker wants to choose an heuristic algorithm which is computationally most efficient algorithm among the proposed algorithms, the variants of greedy heuristic algorithms : SWB, SWB(NARD), SWB(NARD&MIJF) is relatively the best algorithm for Research Problem 1, Research Problem 2 and Research Problem 3 respectively.

Die schichtenübergreifende Steuerung von Multi-Layer Netzen ermöglicht die Realisierung fortgeschrittener Netzarchitekturen sowie neuartiger Konzepte zur Steigerung der Ausfallsicherheit. Gegenstand dieser Arbeit ist ein neues ressourcensparendes Konzept zur Kompensation von Core-Router-Ausfallen in IP-Netzen. Core-Router-Ausfälle führen zur Abkopplung der an Ihnen angeschlossenen Zugangsrouter vom Netz. Daher werden die Zugangsrouter üblicherweise mit jeweils zwei oder mehreren verschiedenen Core-Routern verbunden (engl.: dual homing) was jedoch eine Verdoppelung der Anschlusskapazität im IP Netz bedingt. Bei dem neuen Verfahren - Dual Homing mit gemeinsam genutzten Router-Ersatzressourcen (engl.: dual homing with shared backup router resources, DH-SBRR) - erfolgt die Zugangsrouter-Anbindung zum einen zu einem Core-Router des IP-Netzes und zum anderen zu einem Netzelement der darunterliegenden Transportschicht. Damit lassen sich Router-Ersatzressourcen, die im IP-Netz an beliebigen Stellen vorgehalten werden können, uber das Transportnetz an die Stelle eines ausgefallenen Core-Routers schalten. Die Steuerung dieser Ersatzschaltung geschieht über eine schichten übergreifende, d.h. das Transportnetz- und IP-Netz umfassende Control-Plane - beispielsweise auf Basis von GMPLS. Da beim Umschalten der Routerressourcen auch aktuelle Zustände (bspw. Routing-Tabellen) auf die Router-Ersatzressourcen mit übertragen werden müssen, beinhaltet das neue Verfahren auch Konzepte zur Router-Virtualisierung. Zum Vergleich und zur Bewertung der Leistungsfähigkeit des neuen DH-SBRR Verfahrens werden in der Arbeit verschiedene Zugangsrouter-Homing-Varianten hinsichtlich Netz-Kosten, Netz-Verfügbarkeit, Recovery-Zeit und Netz-Energieverbrauch gegenübergestellt. Als Multi-Layer Netzszenarien werden zum einen IP über WDM und zum anderen IP über OTN (ODU) betrachtet. Zur Bestimmung der minimalen Netz-Kosten ist ein generisches Multi-Layer Netzoptimierungsmodell entwickelt worden, welches bei unterschiedlichen Homing-Architekturen angewendet werden kann. Neben dem Optimierungsmodell zur Netzkostenminimierung wird auch eine Modellvariante zur Minimierung des Energieverbrauchs vorgestellt. Um die Rechenzeit für die Lösung der Optimierungsprobleme zu verringern und damit auch größere Netzszenarien untersuchen zu können bedarf es heuristischer Lösungsverfahren. Im Rahmen der Arbeit ist daher eine neue speziell auf die Multilayer-Optimierungsprobleme zugeschnittene Lösungsheuristik entwickelt worden. Aus der Netzkosten-Optimierung ergibt sich, dass durch den Einsatz von DH-SBBR signifikante Kosteneinsparungen im Vergleich zu herkömmlichen Homing-Architekturen realisiert werden können. Änderungen der Verkehrslast, der Kosten der IP-Netzelemente oder der Netztopologie haben keinen signifikanten Einfluss auf dieses Ergebnis. Neben dem Kosten- und Energieeinsparungspotential sind auch die Auswirkungen auf die Netz-Verfügbarkeit und die Recovery-Zeit untersucht worden. Für die Ende-zu-Ende Verfügbarkeit bei Anwendung der verschiedenen Homing-Architekturen Können untere Grenzwerte angegeben werden. Zur Bestimmung der Recovery-Zeit bei Einsatz von DH-SBRR ist ein eigenes analytisches Berechnungsmodell entwickelt und evaluiert worden. Damit kann das DH-SBRR Verfahren zur Einhaltung vorgegebener Recovery-Zeiten (wie sie für bspw. Für bestimmte Dienste gefordert werden) entsprechend parametriert werden. / The emergence of multi-layer networking capabilities opens the path for the development of advanced network architectures and resilience concepts. In this dissertation we propose a novel resource-efficient homing scheme: dual homing with shared backup router resources. The proposed scheme realizes shared router-level redundancy, enabled by the emergence of control plane architectures such as generalized multi-protocol label switching. Additionally, virtualization schemes complement the proposed architecture. Different homing architectures are examined and compared under the prism of cost, availability, recovery time and energy efficiency. Multiple network layers are considered in Internet protocol over wavelength division multiplexing as well as Internet protocol over optical data unit settings - leading to the development of multi-layer optimization techniques. A generic multi-layer network design mathematical model, which can be applied to different homing architecture considerations, is developed. The optimization objective can be adapted to either minimizing the cost for network equipment or the power consumption of the network. In order to address potential issues with regard to computational complexity, we develop a novel heuristic approach specifically targeting the proposed architecture. It is shown that significant cost savings can be achieved - even under extreme changes in the traffic demand volume, in the cost for different types of network equipment, as well as in the network topology characteristics. In order to evaluate occurring tradeoffs in terms of performance, we study the effects on availability and recovery time. We proceed to derive lower bounds on end-to-end availability for the different homing architectures. Additionally, an analytical recovery time model is developed and evaluated. We investigate how service-imposed maximum outage requirements have a direct effect on the setting of the proposed architecture.

Orientador: Rubén Augusto Romero Lázaro / Resumo: Neste trabalho, consideram-se a análise teórica e a implementação computacional dos algoritmos Primal Simplex Canalizado (PSC) e Dual Simplex Canalizado (DSC) especializados. Esses algoritmos foram incorporados em um algoritmo Branch and Bound (B&B) de modo a resolver o problema de Planejamento da Expansão de Sistemas de Transmissão (PEST). Neste caso, o problema PEST foi modelado usando os chamados modelo de Transportes e modelo Linear Disjuntivo (LD), o que produz um problema de Programação Linear Inteiro Misto (PLIM). O algoritmo PSC é utilizado na resolução do problema de Programação Linear (PL) inicial após desconsiderar a restrição de integralidade do problema PLIM original. Juntamente com o algoritmo PSC, foi implementada uma estratégia para reduzir o número de variáveis artificiais adicionadas ao PL, consequentemente reduzindo o número de iterações do algoritmo PSC. O algoritmo DSC é utilizado na reotimização eficiente dos subproblemas gerados pelo algoritmo B&B, através do quadro ótimo do PL inicial, excluindo, assim, a necessidade da resolução completa de cada subproblema e, consequentemente, reduzindo o consumo de processamento e memória. Nesta pesquisa, é apresentada uma nova proposta de otimização, e, consequentemente, a implementação computacional usando a linguagem de programação FORTRAN que opera independentemente de qualquer solver. / Doutor

Le problème d’approvisionnement conjoint (JDP) proposé est un problème de planification des tournées de livraisons sur un horizon de temps décomposé en périodes élémentaires, l’horizon de temps étant la période commune de livraison de tous les produits,. La donnée de ces paramètres permet d’obtenir une formulation linéaire du problème, avec des variables de décision binaires. Le modèle intègre aussi des contraintes de satisfaction de la demande à partir des stocks et des quantités livrées, des contraintes sur les capacités de stockage et de transport.Afin de résoudre aussi le problème de choix des tournées de livraison, il est nécessaire d'introduire dans le modèle des contraintes et des variables liées aux sites visités au cours de chaque tour. Il est proposé de résoudre le problème en deux étapes. La première étape est le calcul hors ligne du coût minimal de la tournée associé à chaque sous-ensemble de sites. On peut observer que pour tout sous-ensemble donné de sites, le cycle hamiltonien optimal reliant ces sites à l'entrepôt peut être calculé à l'avance par un algorithme du problème du voyageur de commerce (TSP). Le but ici n'est pas d'analyser pleinement le TSP, mais plutôt d'intégrer sa solution dans la formulation de JRP. .Dans la deuxième étape, des variables binaires sont associées à chaque tour et à chaque période pour déterminer le sous-ensemble de sites choisi à chaque période et son coût fixe associé. / The proposed joint delivery problem (JDP) is a delivery tour planning problem on a time horizon decomposed into elementary periods or rounds, the time horizon being the common delivery period for all products. The data of these parameters provides a linear formulation of the problem, with binary decision variables. The model also incorporates the constraints of meeting demand from stock and the quantities supplied, storage and transport capacity constraints.In order to also solve the problem of choice of delivery rounds, it is necessary to introduce in the model several constraints and variables related to the sites visited during each round. It is proposed to solve the problem in two steps. The first step is the calculation of the minimum off-line cost of the tour associated with each subset of sites. One can observe that for any given subset of sites, the optimal Hamiltonian cycle linking those sites to the warehouse can be calculated in advance by a traveling salesman problem algorithm (TSP). The goal here is not to fully analyze the TSP, but rather to integrate its solution in the formulation of the JRP. In the second stage, binary variables are associated with each subset and each period to determine the selected subset of sites in each period and its associated fixed cost.

[pt] Portfólios de fontes renováveis de energia elétrica são mecanismos de gerenciamento de risco interessantes para comercialização de energia em mercados de negociação bilateral. Quando formados por agentes que pertencem a diferentes companhias sua estabilidade depende da maneira com que os benefícios de mitigação de risco gerados pelo portfólio são alocados individualmente entre os participantes. O problema de se encontrar uma solução estável pode ser matematicamente formulado através da busca de um vetor de alocação de quotas que pertença ao núcleo do jogo cooperativo, que por sua vez pode ser formulado como um conjunto de restrições lineares que aumenta exponencialmente com o número de participantes. Adicionalmente, o lado direito de cada restrição que define o núcleo do jogo cooperativo define o valor de uma determinada coalisão que, no presente trabalho, é obtido através de um modelo de otimização estocástica de dois estágios. Este trabalho compara diferentes metodologias computacionalmente eficientes baseadas em programação linear inteira mista e na técnica de decomposição de Benders para encontrar vetores de alocação de quotas que pertençam ao núcleo de portfólios de larga escala de geradores de energia renovável. São apresentados estudos de casos que utilizam dados reais do sistema elétrico brasileiro. / [en] Portfolios of renewable electricity sources are interesting risk-management mechanisms for trading in electricity contract markets. When they are formed by players belonging to different companies, their stability relies on the way the riskmitigation benefit generated by the optimal portfolio is allocated through individual participants. The problem of reaching a stable allocation can be mathematically formulated in terms of finding a quota-sharing vector belonging to the Core of a cooperative game, which can be formulated as a set of linear constraints that exponentially grows with the number of participants. Moreover, the right-hand-side of each constraint defining the Core relies on a given coalition value which, in the present work, is obtained by a two-stage stochastic optimization model. This work presents and compares efficient methodologies mainly based on mixed integer linear programming and Benders decomposition to find quota allocation vectors that belongs to the Core of large-scale renewable energy portfolios. Case studies are presented with realistic data from the Brazilian power system.

Submitted by JEFERSON BACK VANDERLINDE null (jefersonbv@yahoo.com.br) on 2017-11-01T16:38:25Z No. of bitstreams: 1 jeferson_tese_final_20171101.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-11-13T15:38:34Z (GMT) No. of bitstreams: 1 vanderlinde_jb_dr_ilha.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) / Made available in DSpace on 2017-11-13T15:38:34Z (GMT). No. of bitstreams: 1 vanderlinde_jb_dr_ilha.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) Previous issue date: 2017-09-06 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Neste trabalho, consideram-se a análise teórica e a implementação computacional dos algoritmos Primal Simplex Canalizado (PSC) e Dual Simplex Canalizado (DSC) especializados. Esses algoritmos foram incorporados em um algoritmo Branch and Bound (B&B) de modo a resolver o problema de Planejamento da Expansão de Sistemas de Transmissão (PEST). Neste caso, o problema PEST foi modelado usando os chamados modelo de Transportes e modelo Linear Disjuntivo (LD), o que produz um problema de Programação Linear Inteiro Misto (PLIM). O algoritmo PSC é utilizado na resolução do problema de Programação Linear (PL) inicial após desconsiderar a restrição de integralidade do problema PLIM original. Juntamente com o algoritmo PSC, foi implementada uma estratégia para reduzir o número de variáveis artificiais adicionadas ao PL, consequentemente reduzindo o número de iterações do algoritmo PSC. O algoritmo DSC é utilizado na reotimização eficiente dos subproblemas gerados pelo algoritmo B&B, através do quadro ótimo do PL inicial, excluindo, assim, a necessidade da resolução completa de cada subproblema e, consequentemente, reduzindo o consumo de processamento e memória. Nesta pesquisa, é apresentada uma nova proposta de otimização, e, consequentemente, a implementação computacional usando a linguagem de programação FORTRAN que opera independentemente de qualquer solver. / In this research, the theoretical analysis and computational implementation of the specialized dual simplex algorithm (DSA) and primal simplex algorithm (PSA) for bounded variables is considered. These algorithms have been incorporated in a Branch and Bound (B&B) algorithm to solve the Transmission Network Expansion Planning (TNEP) problem. In this case, the TNEP problem is modeled using transportation model and linear disjunctive model (DM), which produces a mixed-integer linear programming (MILP) problem. After relaxing the integrality of investment variables of the original MILP problem, the PSA is used to solve the initial linear programming (LP) problem. Also, it has been implemented a strategy in PSA to reduce the number of artificial variables which are added into the LP problem, and consequently reduces the number of iterations of PSA. Through optimal solution of the initial LP, the DSA is used in efficient reoptimization of subproblems, resulting from the B&B algorithm, thus excludes the need for complete resolution of each subproblems, which results reducing the CPU time and memory consumption. This research presents the implementation of the proposed approach using the FORTRAN programming language which operates independently and does not use any commercial solver.

O objetivo de estudo desta dissertação é o desenvolvimento de um modelo de planejamento agregado da produção que apóie as decisões de nível gerencial e de diretoria das usinas de açúcar e álcool no que tange às variedades de cana colhidas em cada semana, às compras de cana-de-açúcar de terceiros, ao tipo de transporte (próprio ou terceirizado) a se utilizar em cada semana, ao total de cana moída por semana para atendimento da demanda e aos processos (industrial e comercial) que se devem escolher para produzir e comercializar açúcar e álcool. As decisões devem ocorrer em função de preços nos mercados interno, externo e mercado futuro, do fluxo de caixa da empresa, da capacidade da usina para armazenar açúcar e álcool e da possibilidade de uso de estoque de terceiros. As decisões por compra de cana, escolha de processos e venda de produtos são tomadas semanalmente num horizonte móvel de planejamento de 52 semanas, que inclui o tempo de safra no centro-sul do Brasil (meados de março a meados de dezembro, aproximadamente 36 semanas) mais o período de entressafra (aproximadamente 16 semanas, de meados de dezembro a meados de março). A procura por melhores estratégias de comercialização de tal forma a auxiliar a tomada de decisões é uma necessidade constante dos empresários do setor, que muitas vezes são surpreendidos pelas variações de preços de açúcar e álcool no mercado interno, externo e mercado futuro. Na parte comercial, este trabalho utiliza o método Delphi de previsão de preços de açúcar e álcool que balizam as tomadas de decisão no planejamento e controle da produção das usinas de açúcar e álcool. Define-se Hedge como a operação financeira de proteger determinado ativo de uma empresa contra variações inesperadas de preços. Neste trabalho, utiliza-se um modelo de escolha de mix de produto para Hedge vinculado à lucratividade e minimização de risco denominado Modelo de Semi- Variância com análise de cenários de Markowitz. Nas decisões relacionadas com as partes agrícola, industrial e comercial, faz-se uso de um modelo de programação linear inteira mista e para resolvê-lo utiliza-se o software de programação matemática LINGO e suas interfaces com a planilha eletrônica Excel. Nas decisões vinculadas ao mix ótimo para o Hedge em cada semana, faz-se uso de um modelo de programação quadrática resolvido pelo LINGO e suas interfaces com a planilha eletrônica Excel. Um estudo de caso foi realizado numa usina de açúcar e álcool no município de Junqueirópolis (SP) para validar o modelo proposto. / The objective of study this dissertation is to develop a model of aggregate production planning to support the decisions of management and board level of sugar and alcohol plants in regard to varieties of cane harvested each week, purchasing cane of nonsugar, the type of transport (own or outsourced) to use each week, the total cane processed per week for taking care of the demand and processes (industrial and commercial) and that must be chosen to produce and sell sugar and alcohol. Decisions must occur in terms of domestic, foreign and future market prices, the company\'s cash flow and the capacity to store sugar and alcohol and the possibility of using stock to third parties. Decisions about buying cane, choice of processes and products for sale are made in a weekly mobile planning horizon of 52 weeks, which includes the time of harvest in central-southern Brazil (mid-March to mid-December, approximately 36 weeks) plus the off-season (approximately 16 weeks, from mid-December to mid March). The demand for better marketing strategies to help such decision making is a constant need for entrepreneurs in the sector, which are often surprised by the changes in prices of sugar and alcohol in the internal, external and future market. In the commercial part, this study uses the Delphi method of forecasting the price of sugar and alcohol that guides the decision-making in planning and controlling the production of sugar and alcohol plants. Hedging is defined as a financial transaction to protect certain assets of a business against unexpected changes in prices. In this work, it is used a model of choice of product mix for Hedge linked to profitability and minimizing risk named Model of Semi-Variance analysis with scenarios of Markowitz. In decisions related to the agricultural, industrial and commercial parts it is used a type of mixed integer linear programming and to solve it is used the mathematical programming software LINGO and its interface with Excel spreadsheets. In decisions related to the optimal mix for Hedge in each week, is used a quadratic programming model solved by LINGO and its interface with Excel spreadsheets. A case study was conducted in a sugar mill and alcohol in the city of Junqueirópolis (SP) to validate the proposed model.

O ambiente de produção abordado neste trabalho é o Job Shop Flexível (JSF), uma generalização do Job Shop (JS). O problema de programação de tarefas, ou jobs, no ambiente JS é classificado por Garey; Johnson e Sethi (1976) como NP-Difícil e o JSF é, no mínimo, tão difícil quanto o JS. O JSF é composto por um conjunto de jobs, cada qual constituído por operações. Cada operação deve ser processada individualmente, sem interrupção, em uma única máquina de um subconjunto de máquinas habilitadas. O principal critério de desempenho considerado é a minimização dos atrasos dos jobs. São apresentados modelos de Programação Linear Inteira Mista (PLIM) para minimizar o atraso total e o instante de término da última operação, o makespan. São propostas novas regras de prioridade dos jobs, além de adaptações de regras da literatura. Tais regras são utilizadas por heurísticas construtivas e são aliadas a estratégias cujo objetivo é explorar características específicas do JSF. Visando aprimorar as soluções inicialmente obtidas, são propostas buscas locais e outros mecanismos de melhoria utilizados no desenvolvimento de três meta-heurísticas de diferentes categorias. Essas meta-heurísticas são: Iterated Local Search (ILS), classificada como meta-heurística de trajetória; Greedy Randomized Adaptive Search (GRASP), meta-heurística construtiva; e Artificial Bee Colony (ABC), meta-heurística populacional recentemente proposta. Esses métodos foram selecionados por alcançarem bons resultados para diversos problemas de otimização da literatura. São realizados experimentos computacionais com 600 instâncias do JSF, permitindo comparações entre os métodos de resolução. Os resultados mostram que explorar as características do problema permite que uma das regras de prioridade propostas supere a melhor regra da literatura em 81% das instâncias. As meta-heurísticas ILS, GRASP e ABC chegam a conseguir mais de 31% de melhoria sobre as soluções iniciais e a obter atrasos, em média, somente 2,24% superiores aos das soluções ótimas. Também são propostas modificações nas meta-heurísticas que permitem obter melhorias ainda mais expressivas sem aumento do tempo de execução. Adicionalmente é estudada uma versão do JSF com operações de Montagem e Desmontagem (JSFMD) e os experimentos realizados com um conjunto de 150 instâncias também indicam o bom desempenho dos métodos desenvolvidos. / The production environment addressed herein is the Flexible Job Shop (FJS), a generalization of the Job Shop (JS). In the JS environment, the jobs scheduling problem is classified by Garey; Johnson and Sethi (1976) as NP-Hard and the FJS is at least as difficult as the JS. FJS is composed of a set of jobs, each consisting of operations. Each operation must be processed individually, without interruption, in a single machine of a subset of enabled machines. The main performance criterion is minimizing the jobs tardiness. Mixed Integer Linear Programming (MILP) models are presented. These models minimize the total tardiness and the completion time of the last operation, makespan. New priority rules of jobs are proposed, as well as adaptations of rules from the literature. These rules are used by constructive heuristics and are combined with strategies aimed at exploiting specific characteristics of FSJ. In order to improve the solutions initially obtained, local searches and other improvement mechanisms are proposed and used in the development of metaheuristics of three different categories. These metaheuristics are: Iterated Local Search (ILS), classified as trajectory metaheuristic; Greedy Randomized Adaptive Search (GRASP), constructive metaheuristic, and Artificial Bee Colony (ABC), recently proposed population metaheuristic. These methods were selected owing to their good results for various optimization problems in the literature. Computational experiments using 600 FJS instances are carried out to allow comparisons between the resolution methods. The results show that exploiting the characteristics of the problem allows one of the proposed priority rules to exceed the best literature rule in about 81% of instances. Metaheuristics ILS, GRASP and ABC achieve more than 31% improvement over the initial solutions and obtain an average tardiness only 2.24% higher than the optimal solutions. Modifications in metaheuristics are proposed to obtain even more significant improvements without increased execution time. Additionally, a version called Disassembly and Assembly FSJ (DAFJS) is studied and the experiments performed with a set of 150 instances also indicate good performance of the methods developed.

Ce manuscrit présente des travaux visant à intégrer un module d'ordonnancement (ProSched) à l'environnement de modélisation et simulation dynamique hybride PrODHyS dans le but d'automatiser la génération de scénarii de simulation de procédés discontinus sur la base d'une recette et d'une liste d'ordres de fabrication (OF). La méthodologie développée repose sur une approche mixte optimisation/simulation. Dans ce cadre, trois points essentiels ont été développés dans ces travaux : - tout d'abord, concevoir et développer des composants réutilisables (classes de recette) permettant de modéliser de manière hiérarchisée et systématique le déroulement des opérations unitaires. Pour cela, les notions de jeton Task et de macro-place paramétrable ont été introduites dans les RdPDO et permettent de décrire les recettes à réaliser par assemblage de ces composants prédéfinis. - ensuite, définir un modèle mathématique générique d'ordonnancement basé sur un formalisme de représentation bien établi (le R.T.N.) qui permet de modéliser les principales caractéristiques d'un procédé discontinu et de fournir l'ensemble des données d'entrée nécessaires au modèle de simulation. Pour cela, un modèle PLNE basé sur la formulation Unit Specific Event a été mis en œuvre. - enfin, définir l'interface existant entre le modèle d'optimisation et le modèle de simulation, à travers la notion de place de pilotage et de centre de décision au niveau du simulateur. Dans ce cadre, différentes stratégies de couplage sont proposées. Les potentialités de cette approche sont illustrées par la simulation d'un procédé complet. / This thesis presents works which aim to incorporate a scheduling module (ProSched) to an environment for modeling and dynamic hybrid simulation PrODHyS in order to automate the generation of scenarios for simulation of batch processes based on a recipe and a list of production orders (OF). The methodology developed is based on a mixed optimization / simulation approach. In this context, three key points have been developed in this work: - First, design and develop reusable components (recipe classes) for the hierarchical and systematic modeling of the sequencing of unit operations. For this, the notions of Task token and macro-place have been introduced in the RdPDO formalism and allow the modeling of recipes by assembling these predefined components. - Secondly, define a generic mathematical model of scheduling based on a well defined graphical formalism (RTN) that models the main characteristics of batch processes and provide all input data necessary to the simulation model. For this, a MILP model based on the Unit Specific Event formulation has been implemented. - Finally, define the interface between the optimization model and the simulation model through the concept of control place and decision-making center at the simulator level. In this context, various strategies of mixing optimization and simulation are proposed. The potential of this approach is illustrated by the simulation of a complete manufacturing process