Para uma empresa de navegação, manter uma frota grande de contêineres próprios poderia gerar custos desnecessários para manutenção dos estoques destes contêineres; contudo, se a frota de contêineres próprios for pequena, poderia resultar em um número grande de contêineres arrendados a curto prazo. Assim, nesta dissertação desenvolve-se um modelo de programação linear capaz de estimar a frota ótima de contêineres próprios e alugados, que envolve a dificuldade da tomada de decisão em um comércio extremamente desequilibrado. A revisão bibliográfica apresenta poucas publicações que tratam do tema proposto. O trabalho desenvolvido por Imai e Rivera (2001) é examinado por ser mais semelhante ao tema proposto para esta dissertação. Por tratarem do dimensionamento de frota de contêineres para dois portos e não admitirem aleatoriedades nos tempos de movimentação terrestre de contêineres outros procedimentos foram examinados. Para tentar solucionar o problema de dimensionamento de frota de contêineres próprios para a empresa de navegação dois métodos são analisados: modelo de simulação probabilística e modelo de programação linear. O modelo de simulação é desenvolvido para um problema pequeno. Conforme a ampliação deste modelo e o aumento do número de variáveis, o modelo de simulação passou a ser difícil de ser controlado, pois a mudança dos valores destas variáveis se tornaria muito difícil. O modelo de programação linear é desenvolvido com base nas características e definições adotadas para o modelo de simulação. Este modelo matemático incorpora as aleatoriedades existentes nos processos terrestres, de acordo com as hipóteses adotadas. Este modelo permite auxiliar o planejador a tomar decisões estratégicas, com relação ao tamanho da frota de contêineres necessários para atender a demanda de transporte ao longo do horizonte de planejamento, e operacionais, por apresentar o fluxo de transporte de contêineres vazios entre portos, bem como a quantidade de contêineres alugados, se necessários, para realizar as operações emergenciais associadas a picos de demanda ao longo do período de planejamento. Para testar a consistência do modelo, cenários hipotéticos foram gerados. Por meio dos resultados obtidos para estes cenários, mostra-se a relação do custo dos contêineres alugados e do custo do transporte de contêineres próprios vazios sobre o tamanho da frota de contêineres próprios. / For a carrier, provide a large fleet of owned containers could generate unnecessary costs for maintenance of their inventories; however, if the fleet of owned containers is small, it might result in a large number of short-term leased containers. Thus, it is developed a linear programming model capable to determine the optimal fleet size of owned and leased containers that involves the difficulty of decision-making in an extremely unbalanced trade. The literature survey presents few publications that deal with the considered subject. The work developed for Imai and Rivera (2001) is examined by being more similar to the subject considered in this project. For dealing with the container fleet sizing for two ports and not admitting stochastic travel times inland of containers other procedures are examined. To solve the problem of own container fleet sizing for the carriers two methods are analyzed: probabilistic simulation model and linear programming model. The simulation model is developed for a small problem. As the growing of this model and the increase of the number of variables, the simulation model becomes difficult to control, because the change of the values of these variables would become very hard. The linear programming model is developed on the basis of the characteristics and definitions adopted for the simulation model. This mathematical model incorporates the existing stochastic inland times, in accordance with the adopted hypotheses. This model allows to assist the planner to make strategical decisions, with regard to the size of the fleet of containers necessary to attempt the demand of transport throughout the planning horizon, and operational, for presenting the flow of empty cont ainers between ports, as well as the amount of leased containers, if necessary, to carry through the special operations associated the peaks of demand throughout the period of planning. To test the consistency of the model, hypothetical scenes had been generated. By the results gotten for these scenes, it is showed the relation of the cost of leases containers and the cost of the transport of empty owned containers above the owned container fleet size.

Para uma empresa de navegação, manter uma frota grande de contêineres próprios poderia gerar custos desnecessários para manutenção dos estoques destes contêineres; contudo, se a frota de contêineres próprios for pequena, poderia resultar em um número grande de contêineres arrendados a curto prazo. Assim, nesta dissertação desenvolve-se um modelo de programação linear capaz de estimar a frota ótima de contêineres próprios e alugados, que envolve a dificuldade da tomada de decisão em um comércio extremamente desequilibrado. A revisão bibliográfica apresenta poucas publicações que tratam do tema proposto. O trabalho desenvolvido por Imai e Rivera (2001) é examinado por ser mais semelhante ao tema proposto para esta dissertação. Por tratarem do dimensionamento de frota de contêineres para dois portos e não admitirem aleatoriedades nos tempos de movimentação terrestre de contêineres outros procedimentos foram examinados. Para tentar solucionar o problema de dimensionamento de frota de contêineres próprios para a empresa de navegação dois métodos são analisados: modelo de simulação probabilística e modelo de programação linear. O modelo de simulação é desenvolvido para um problema pequeno. Conforme a ampliação deste modelo e o aumento do número de variáveis, o modelo de simulação passou a ser difícil de ser controlado, pois a mudança dos valores destas variáveis se tornaria muito difícil. O modelo de programação linear é desenvolvido com base nas características e definições adotadas para o modelo de simulação. Este modelo matemático incorpora as aleatoriedades existentes nos processos terrestres, de acordo com as hipóteses adotadas. Este modelo permite auxiliar o planejador a tomar decisões estratégicas, com relação ao tamanho da frota de contêineres necessários para atender a demanda de transporte ao longo do horizonte de planejamento, e operacionais, por apresentar o fluxo de transporte de contêineres vazios entre portos, bem como a quantidade de contêineres alugados, se necessários, para realizar as operações emergenciais associadas a picos de demanda ao longo do período de planejamento. Para testar a consistência do modelo, cenários hipotéticos foram gerados. Por meio dos resultados obtidos para estes cenários, mostra-se a relação do custo dos contêineres alugados e do custo do transporte de contêineres próprios vazios sobre o tamanho da frota de contêineres próprios. / For a carrier, provide a large fleet of owned containers could generate unnecessary costs for maintenance of their inventories; however, if the fleet of owned containers is small, it might result in a large number of short-term leased containers. Thus, it is developed a linear programming model capable to determine the optimal fleet size of owned and leased containers that involves the difficulty of decision-making in an extremely unbalanced trade. The literature survey presents few publications that deal with the considered subject. The work developed for Imai and Rivera (2001) is examined by being more similar to the subject considered in this project. For dealing with the container fleet sizing for two ports and not admitting stochastic travel times inland of containers other procedures are examined. To solve the problem of own container fleet sizing for the carriers two methods are analyzed: probabilistic simulation model and linear programming model. The simulation model is developed for a small problem. As the growing of this model and the increase of the number of variables, the simulation model becomes difficult to control, because the change of the values of these variables would become very hard. The linear programming model is developed on the basis of the characteristics and definitions adopted for the simulation model. This mathematical model incorporates the existing stochastic inland times, in accordance with the adopted hypotheses. This model allows to assist the planner to make strategical decisions, with regard to the size of the fleet of containers necessary to attempt the demand of transport throughout the planning horizon, and operational, for presenting the flow of empty cont ainers between ports, as well as the amount of leased containers, if necessary, to carry through the special operations associated the peaks of demand throughout the period of planning. To test the consistency of the model, hypothetical scenes had been generated. By the results gotten for these scenes, it is showed the relation of the cost of leases containers and the cost of the transport of empty owned containers above the owned container fleet size.

O Brasil possui uma matriz de transporte onde apenas 13% das cargas utilizam vias marítimas, o que não condiz com a realidade de seu território, onde sua extensa área e litoral fazem do modal aquaviário uma importante alternativa na movimentação de cargas. Nesse contexto, o presente trabalho simulou um sistema de cabotagem onde navios circulam entre três portos dedicados, localizados em Suape, Santos e Rio Grande, e tem como objetivo dimensionar o número de berços por porto e a número e tamanho dos navios necessários para transportar, exclusivamente por contêineres, uma parcela da carga rodoviária. O trabalho considera as atividades de pré-operação, operação (carregamento e descarregamento), pós-operação, viagem entre portos e eventuais filas de entrada, em uma abordagem estocástica desses fatores, além do balanceamento e movimentação de contêineres vazios. Os resultados mostram que o tamanho da infraestrutura necessária para a implementação de um sistema dedicado à cabotagem é viável e seria uma alternativa para melhorar o sistema de transporte de carga entre os estados estudados. / Only 13% of Brazilian loads are transported by ships, which does not match the reality of its territory, where its extensive area and coastline make the waterway mode an important alternative in cargo handling. In this context, the present work aims to simulate a short sea shipping system where ships circulate between three dedicated ports, located in Suape, Santos and Rio Grande, in order to size the number of berths per port and the number and size of the ships necessary to transport, exclusively by containers, a portion of the road load. The work considers the pre-operation, operation (loading and unloading), post-operation, travel between ports and eventual entry queues, in a stochastic approach of these factors, and beside that the balancing and movement of empty containers. The results show that the infrastructure size required for the implementation of a short sea shipping system is feasible and would be an alternative to improve the system of cargo transportation among the states studied.

A presente pesquisa aborda o problema de dimensionamento de frota de navios rebocadores do tipo AHTS, que são utilizados essencialmente nas tarefas de operações de apoio à exploração e produção de petróleo offshore (em alto mar). Essas atividades se caracterizam pela requisição simultânea de múltiplos navios de classes diferentes, e possuem parâmetros como: compatibilidade de classes de navios com as tarefas, duração em dias, local de execução e instante desejado de atendimento. Para representar este problema foi desenvolvido um modelo de simulação com parâmetros estocásticos, cuja programação é orientada para minimização dos custos totais da operação, que englobam custos fixos, custos de penalidade por atraso no atendimento das tarefas, e penalidade por falta de cumprimento de tarefas. A abordagem de solução do modelo é a busca exaustiva onde são comparados cenários de simulação de eventos discretos. Adicionalmente, foram comparadas 2 modos de escolhas de tarefas na fila de tarefas, o primeiro é o modo FIFO (First In First Out), o segundo modo é a priorização de tarefas com maior custo de penalidade associado para o dimensionamento de frota. / This research addresses a fleet sizing problem of anchor and handling and tug supply vessels (AHTS), which support the exploration and production of oil at the sea. The support activities are characterized by simultaneous request of multiple vessels of one or more classes. Other characteristics of the research problem are:: the compatibility between vessels and tasks, task duration (in days), a place of execution the task and a desired instant to be attended. A simulation model with stochastic parameters was developed to represent this problem, aiming to minimize the total operational cost that includes fixed costs,penalty costs if tasks are delayed and penalty costs with not completed tasks. The strategy to solve this problem was the exhausted search through discrete-event simulation. Aditionally, 2 methods of approach for the queue were analyzed: the first one is the FIFO (First In First Out) and the second one is the priority according the highest penalty cost to size the fleet.

<p>Nynas produces bitumen at two refineries in Sweden. The bitumen is shipped to seven depots along the swedish coast line, and from the depots special trucks handle the transportation to customers. Recently Nynas has transformed its supply chain and closed down a few depots. At the moment the company is considering a further reduction of the number of depots. In connection to these discussions an analyse of the companys distributionsystem and of possible changes is required. In this thesis an optimization model is developed that simulates Nynas distribution of bitumen from the depots to the customers. The model is used to investigate the required vehicle fleet size for a number of different scenarios, that is with different depots closed down. The question to be answered is, thus, what depots could be closed without any dramatic increase in the required vehicle fleet size? Scenarios where customers are allocated an increased storage capacity are also studied. </p><p>The distribution model that is developed is an inventory route planning problem. It is solved by column generation. Each column represents a route and is generated by a subproblem with restrictions on permitted working hours for the truck drivers. Integer solutions are generated heuristically. </p><p>Simulations that have been performed with the model reveals interesting differences concerning how the distribution is handled in different parts of Sweden. In western Sweden the transportation planning works well, but the distribution in the central parts of the country could be planned in a better way. Results from simulations also show that the depots in Norrköping and Västerås could be closed down without increasing the vehicle fleet. Probably, the existing vehicle fleet size will be sufficient even with the Kalmar-depot closed down. Nevertheless, Nynas transportation suppliers will have to purchase new vehicles if the Sandarne-depot is to be closed. </p><p>Another interesting conclusion that can be drawn from this thesis is that there is a potential for reducing the vehicle fleet size if the storage capacity is increased at a few chosen customers. A considerably small increase in the storage capacity at a few big customers that are located far from the depots will have a great effect.</p>

Nynas produces bitumen at two refineries in Sweden. The bitumen is shipped to seven depots along the swedish coast line, and from the depots special trucks handle the transportation to customers. Recently Nynas has transformed its supply chain and closed down a few depots. At the moment the company is considering a further reduction of the number of depots. In connection to these discussions an analyse of the companys distributionsystem and of possible changes is required. In this thesis an optimization model is developed that simulates Nynas distribution of bitumen from the depots to the customers. The model is used to investigate the required vehicle fleet size for a number of different scenarios, that is with different depots closed down. The question to be answered is, thus, what depots could be closed without any dramatic increase in the required vehicle fleet size? Scenarios where customers are allocated an increased storage capacity are also studied. The distribution model that is developed is an inventory route planning problem. It is solved by column generation. Each column represents a route and is generated by a subproblem with restrictions on permitted working hours for the truck drivers. Integer solutions are generated heuristically. Simulations that have been performed with the model reveals interesting differences concerning how the distribution is handled in different parts of Sweden. In western Sweden the transportation planning works well, but the distribution in the central parts of the country could be planned in a better way. Results from simulations also show that the depots in Norrköping and Västerås could be closed down without increasing the vehicle fleet. Probably, the existing vehicle fleet size will be sufficient even with the Kalmar-depot closed down. Nevertheless, Nynas transportation suppliers will have to purchase new vehicles if the Sandarne-depot is to be closed. Another interesting conclusion that can be drawn from this thesis is that there is a potential for reducing the vehicle fleet size if the storage capacity is increased at a few chosen customers. A considerably small increase in the storage capacity at a few big customers that are located far from the depots will have a great effect.

Transportation is one of the most vital services in modern society. It makes most of the other functions of society possible. Real transportation systems are so large and complex that in order to build the science of transportation systems it will be necessary to work in many areas, such as: Modeling, Optimization and Simulation. We are interested in solutions for the so-called fleet-sizing-and-allocation problem (FSAP). Fleet sizing and allocation problems are one of the most interesting and hard to solve logistic problems. A fleet sizing and allocation problem consists of two interdependent parts. The fleet sizing problem is to determine a number of transportation units that optimally balances service requirements against the cost of purchasing and maintaining the transportation units. The allocation problem is dealing with the repositioning of transportation units to serve future transportation demand. To make the fleet sizing and allocation problem a little bit more tractable we concentrate on logistic systems with a special hub-and-spoke structure. We start with a very simple fleet sizing of one-to-one case. This case will cause us to focus attention on several key issues in fleet sizing. Afterwards, the generalization of the one-to-one system is the one-to-many system. As a simple example can serve the continuous time situation where a single origin delivers items to many destinations. For the case that items are produced in a deterministic production cycle and transportation times are stochastic. We also studied a hub-and-spoke problem with continuous time and stochastic demand. To solve this problem, based on Marginal Analysis, we applied queueing theory methods. The investigation of the fleet-sizing-and-allocation problem for hub-and-spoke systems is started for a single-period, deterministic-demand model. In that the model hub has to decide how to use a given number of TU’s to satisfy a known (deterministic) demand in the spokes. We consider two cases: 1. Renting of additional TU’s from outside the system is not possible, 2. Renting of additional TU’s from outside the system is possible. For each case, based on Marginal Analysis, we developed a simple algorithm, which gives us the cost-minimal allocation. Since the multi-period, deterministic demand problem is NP-hard we suggest to use Genetic Algorithms. Some building elements for these are described. For the most general situation we also suggest to use simulation optimization. To realize the simulation optimization approach we could use the software tool “Calculation Assessment Optimization System” (CAOS). The idea of CAOS is to provide a software system, which separates the optimization process from the optimization problem. To solve an optimization problem the user of CAOS has to build up a model of the system to which the problem is related. Furthermore he has to define the decision parameters and their domain. Finally, we used CAOS for two classes of hub-and-spoke system: 1. A single hub with four spokes, 2. A single hub with fifty spokes. We applied four optimizers – a Genetic Algorithm, Tabu Search, Hybrid Parallel and Hybrid Serial with two distributions (Normal Distribution and Exponential Distribution) for a customer interarrival times and their demand.

A presente pesquisa aborda o problema de dimensionamento de frota de navios rebocadores do tipo AHTS, que são utilizados essencialmente nas tarefas de operações de apoio à exploração e produção de petróleo offshore (em alto mar). Essas atividades se caracterizam pela requisição simultânea de múltiplos navios de classes diferentes, e possuem parâmetros como: compatibilidade de classes de navios com as tarefas, duração em dias, local de execução e instante desejado de atendimento. Para representar este problema foi desenvolvido um modelo de simulação com parâmetros estocásticos, cuja programação é orientada para minimização dos custos totais da operação, que englobam custos fixos, custos de penalidade por atraso no atendimento das tarefas, e penalidade por falta de cumprimento de tarefas. A abordagem de solução do modelo é a busca exaustiva onde são comparados cenários de simulação de eventos discretos. Adicionalmente, foram comparadas 2 modos de escolhas de tarefas na fila de tarefas, o primeiro é o modo FIFO (First In First Out), o segundo modo é a priorização de tarefas com maior custo de penalidade associado para o dimensionamento de frota. / This research addresses a fleet sizing problem of anchor and handling and tug supply vessels (AHTS), which support the exploration and production of oil at the sea. The support activities are characterized by simultaneous request of multiple vessels of one or more classes. Other characteristics of the research problem are:: the compatibility between vessels and tasks, task duration (in days), a place of execution the task and a desired instant to be attended. A simulation model with stochastic parameters was developed to represent this problem, aiming to minimize the total operational cost that includes fixed costs,penalty costs if tasks are delayed and penalty costs with not completed tasks. The strategy to solve this problem was the exhausted search through discrete-event simulation. Aditionally, 2 methods of approach for the queue were analyzed: the first one is the FIFO (First In First Out) and the second one is the priority according the highest penalty cost to size the fleet.

A racionalização no uso dos recursos sempre foi uma preocupação dos gestores de empresas e com a crescente competitividade entre essas organizações, faz-se necessário, portanto, um controle minucioso dos custos. Empresas do ramo florestal lidam todos os dias com problemas desde o nível estratégico, como a decisão de em quais regiões realizarem o plantio das árvores, até o nível operacional, que tem maior impacto sobre as operações diárias e que envolve as decisões de transporte de madeira. Nesse sentido, o investimento em ferramentas que garantam maior eficiência do transporte diário de madeira é considerado como ponto de partida para que essas organizações possam sustentar sua competitividade no mercado. Dessa forma, esta dissertação tem como objetivo dimensionar, através de um modelo de simulação, a frota de caminhões utilizada para o transporte diário de madeira em uma indústria de papel e celulose, com vistas a permitir um fluxo coordenado e constante de matéria prima, comparando o sistema atual com um sistema baseado em uma nova lógica de despacho de caminhões aplicada ao simulador. O modelo de simulação desenvolvido foi construído através do software ARENA® e conta com uma interface de dados construída com o auxílio do Microsoft Excel®, na qual são inseridos, de maneira estruturada, os dados de entrada necessários. Com este modelo, pretende-se auxiliar na solução de um problema operacional de transporte de madeira, uma vez que é possível determinar, em um horizonte de planejamento previamente definido, o tamanho da frota capaz de atender a uma demanda programada, permitindo maior eficiência ao sistema e redução de desperdícios. / The rational use of resources has always been a concern of business managers and the growing competition between companies requires a complex control of costs. Companies in the forestry sector deal with everyday problems from the strategic level, the decision on which regions make the planting of trees, to the operational level, which has a greater impact on the daily operations and decisions involving timber transport. Accordingly, investment in tools that ensure higher efficiency of daily transportation of wood is considered as the starting point for these organizations to sustain their competitiveness in the market. Thus, this thesis is designed to measure, through a simulation model, the fleet of trucks used for daily transportation of wood into a pulp and paper industry, with a view to providing coordinated and constant flow of raw material. The developed simulation model was built by ARENA ® software and has a data interface built with the help of Microsoft ® Excel, in which the input data required are inserted. With this model, we intend to assist in the solution of an operating problem of timber transport, since it is possible to determine the fleet size able to attend a scheduled demand, allowing the system more efficient and reduce waste, in a planning horizon previously defined.

A racionalização no uso dos recursos sempre foi uma preocupação dos gestores de empresas e com a crescente competitividade entre essas organizações, faz-se necessário, portanto, um controle minucioso dos custos. Empresas do ramo florestal lidam todos os dias com problemas desde o nível estratégico, como a decisão de em quais regiões realizarem o plantio das árvores, até o nível operacional, que tem maior impacto sobre as operações diárias e que envolve as decisões de transporte de madeira. Nesse sentido, o investimento em ferramentas que garantam maior eficiência do transporte diário de madeira é considerado como ponto de partida para que essas organizações possam sustentar sua competitividade no mercado. Dessa forma, esta dissertação tem como objetivo dimensionar, através de um modelo de simulação, a frota de caminhões utilizada para o transporte diário de madeira em uma indústria de papel e celulose, com vistas a permitir um fluxo coordenado e constante de matéria prima, comparando o sistema atual com um sistema baseado em uma nova lógica de despacho de caminhões aplicada ao simulador. O modelo de simulação desenvolvido foi construído através do software ARENA® e conta com uma interface de dados construída com o auxílio do Microsoft Excel®, na qual são inseridos, de maneira estruturada, os dados de entrada necessários. Com este modelo, pretende-se auxiliar na solução de um problema operacional de transporte de madeira, uma vez que é possível determinar, em um horizonte de planejamento previamente definido, o tamanho da frota capaz de atender a uma demanda programada, permitindo maior eficiência ao sistema e redução de desperdícios. / The rational use of resources has always been a concern of business managers and the growing competition between companies requires a complex control of costs. Companies in the forestry sector deal with everyday problems from the strategic level, the decision on which regions make the planting of trees, to the operational level, which has a greater impact on the daily operations and decisions involving timber transport. Accordingly, investment in tools that ensure higher efficiency of daily transportation of wood is considered as the starting point for these organizations to sustain their competitiveness in the market. Thus, this thesis is designed to measure, through a simulation model, the fleet of trucks used for daily transportation of wood into a pulp and paper industry, with a view to providing coordinated and constant flow of raw material. The developed simulation model was built by ARENA ® software and has a data interface built with the help of Microsoft ® Excel, in which the input data required are inserted. With this model, we intend to assist in the solution of an operating problem of timber transport, since it is possible to determine the fleet size able to attend a scheduled demand, allowing the system more efficient and reduce waste, in a planning horizon previously defined.