A rapidez na realização do atendimento às vítimas é uma das maiores necessidades de serviços de atendimento médico de urgência, e o tempo decorrido entre o instante da ocorrência da solicitação pelo serviço e o início do atendimento, denominado tempo de resposta, é um dos principais fatores que influenciam o desempenho do sistema. Este tempo depende de uma reunião de fatores como condições de tráfego, dia e período do dia, número de veículos disponíveis e suas localizações, capacitação profissional da equipe, etc. Apresenta-se neste trabalho uma análise do desempenho do serviço oferecido na cidade de Campinas-SP, tratando o problema por meio do modelo hipercubo de filas, que considera as variações aleatórias dos processos de chegadas e atendimento dos chamados. Sua aplicação produz uma ampla variedade de indicadores de desempenho para o sistema, que são comparados com os valores reais observados, para validar a hipótese de aplicação do modelo. Os resultados de sua aplicação para configurações operacionais alternativas, tais como descentralização e aumento do número de ambulâncias, mostraram uma elevação significativa do nível de serviço oferecido ao usuário. Conclui-se que o modelo constitui uma importante ferramenta de análise para este tipo de sistema, auxiliando na tomada de decisões estratégicas e operacionais do sistema. / One of the major concerns of medical emergency systems is to provide the fastest possible medical attention for the victims. The time elapsed between the emergency call and the assistance, called the response time, is one of the main factors that influence the system\'s performance. This time lapse depends on traffic conditions, the day of the week and time of day, the number of available vehicles and their location, the rescue team\'s professional qualifications, etc. This work consists of an analysis of the performance of the emergency service available in Campinas, SP, and deals with the problem using the hypercube queuing model, which considers stochastic variations of the arrival and assistance processes. The application of this model produces a wide variety of system performance indicators, which are compared with the real observed values to validate the model\'s hypothetical application. Application of the model in alternative operational scenarios, such as decentralization and a greater number of ambulances, showed a significant increase in the quality of the service offered to the user. It was concluded that the model constitutes an important analytical tool for this type of system, serving as an aid for strategic and operational decision-making.

A rapidez na realização do atendimento às vítimas é uma das maiores necessidades de serviços de atendimento médico de urgência, e o tempo decorrido entre o instante da ocorrência da solicitação pelo serviço e o início do atendimento, denominado tempo de resposta, é um dos principais fatores que influenciam o desempenho do sistema. Este tempo depende de uma reunião de fatores como condições de tráfego, dia e período do dia, número de veículos disponíveis e suas localizações, capacitação profissional da equipe, etc. Apresenta-se neste trabalho uma análise do desempenho do serviço oferecido na cidade de Campinas-SP, tratando o problema por meio do modelo hipercubo de filas, que considera as variações aleatórias dos processos de chegadas e atendimento dos chamados. Sua aplicação produz uma ampla variedade de indicadores de desempenho para o sistema, que são comparados com os valores reais observados, para validar a hipótese de aplicação do modelo. Os resultados de sua aplicação para configurações operacionais alternativas, tais como descentralização e aumento do número de ambulâncias, mostraram uma elevação significativa do nível de serviço oferecido ao usuário. Conclui-se que o modelo constitui uma importante ferramenta de análise para este tipo de sistema, auxiliando na tomada de decisões estratégicas e operacionais do sistema. / One of the major concerns of medical emergency systems is to provide the fastest possible medical attention for the victims. The time elapsed between the emergency call and the assistance, called the response time, is one of the main factors that influence the system\'s performance. This time lapse depends on traffic conditions, the day of the week and time of day, the number of available vehicles and their location, the rescue team\'s professional qualifications, etc. This work consists of an analysis of the performance of the emergency service available in Campinas, SP, and deals with the problem using the hypercube queuing model, which considers stochastic variations of the arrival and assistance processes. The application of this model produces a wide variety of system performance indicators, which are compared with the real observed values to validate the model\'s hypothetical application. Application of the model in alternative operational scenarios, such as decentralization and a greater number of ambulances, showed a significant increase in the quality of the service offered to the user. It was concluded that the model constitutes an important analytical tool for this type of system, serving as an aid for strategic and operational decision-making.

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.

Information-theoretic arguments focus on modeling the reliability of information transmission, assuming availability of infinite data at sources, thus ignoring randomness in message generation times at the respective sources. However, in information transport networks, not only is reliable transmission important, but also stability, i.e., finiteness of mean delay in- curred by messages from the time of generation to the time of successful reception. Usually, delay analysis is done separately using queueing-theoretic arguments, whereas reliable information transmission is studied using information theory. In this thesis, we investigate these two important aspects of data communication jointly by suitably combining models from these two fields. In particular, we model scheduled communication of messages , that arrive in a random process, (i) over multiaccess channels, with either independent decoding or joint decoding, and (ii) over degraded broadcast channels. The scheduling policies proposed permit up to a certain maximum number of messages for simultaneous transmission. In the first part of the thesis, we develop a multi-class discrete-time processor-sharing queueing model, and then investigate the stability of this queue. In particular, we model the queue by a discrete-time Markov chain defined on a countable state space, and then establish (i) a sufficient condition for c-regularity of the chain, and hence positive recurrence and finiteness of stationary mean of the function c of the state, and (ii) a sufficient condition for transience of the chain. These stability results form the basis for the conclusions drawn in the thesis. The second part of the thesis is on multiaccess communication with random message arrivals. In the context of independent decoding, we assume that messages can be classified into a fixed number of classes, each of which specifies a combination of received signal power, message length, and target probability of decoding error. Each message is encoded independently and decoded independently. In the context of joint decoding, we assume that messages can be classified into a fixed number of classes, each of which specifies a message length, and for each of which there is a message queue. From each queue, some number of messages are encoded jointly, and received at a signal power corresponding to the queue. The messages are decoded jointly across all queues with a target probability of joint decoding error. For both independent decoding and joint decoding, we derive respective discrete- time multiclass processor-sharing queueing models assuming the corresponding information-theoretic models for the underlying communication process. Then, for both the decoding schemes, we (i) derive respective outer bounds to the stability region of message arrival rate vectors achievable by the class of stationary scheduling policies, (ii) show for any mes- sage arrival rate vector that satisfies the outer bound, that there exists a stationary “state-independent” policy that results in a stable system for the corresponding message arrival process, and (iii) show that the stability region of information arrival rate vectors, in the limit of large message lengths, equals an appropriate information-theoretic capacity region for independent decoding, and equals the information-theoretic capacity region for joint de-coding. For independent decoding, we identify a class of stationary scheduling policies, for which we show that the stability region in the limit of large maximum number of simultane-ous transmissions is independent of the received signal powers, and each of which achieves a spectral efficiency of 1 nat/s/Hz in the limit of large message lengths. In the third and last part of the thesis, we show that the queueing model developed for multiaccess channels with joint decoding can be used to model communication over degraded broadcast channels, with superposition encoding and successive decoding across all queues. We then show respective results (i), (ii), and (iii), stated above.

Made available in DSpace on 2016-06-02T19:50:01Z (GMT). No. of bitstreams: 1 TeseJGSR.pdf: 2611645 bytes, checksum: 6dbd36dc8e39b96d32bfddfeef61b88a (MD5) Previous issue date: 2007-06-29 / Self-service companies have been concerned about improving their performance in face of competition, either to conquer new markets or to keep in business. It is essential for them to present good quality products and/or services. Thus, in this study, one of the aims was to show that the waiting time in supermarket checkout lines is very important for service speed and, therefore, for the service level of customers. Other aims include the reasons why the customer goes regularly to a specific supermarket and, among these reasons, the relevance of each one in contrast with the others, and its relative importance. As a result, it was possible to contextualize the scenario in which customers view the importance of queues and their waiting time. Also, the level of schooling of the customers was associated with the factors that lead them to go regularly to the place. This is an interesting contribution because in Brazil there is a relation between income and schooling. Besides, the queueing models that may satisfactorily represent the supermarket checkouts were studied and the one that best represents the system was identified. It was verified that the customers change lines when they notice another line with fewer customers, and the size of this difference was assessed. The queueing model with jockeying was the one to best represent the situation commonly found in supermarkets, and it can offer subsidies for service improvement. In order to carry out this research some companies in the city of São Carlos/SP were contacted, and one among the ones that allowed the data collection was selected. Therefore, this is a case study, thus presenting inferential limitations. / As empresas de auto-serviço, em geral, têm se preocupado em melhorar seu desempenho em relação à concorrência, seja para ganhar mercado ou mesmo para sobreviver. É essencial que apresentem boa qualidade nos produtos oferecidos e/ou serviços prestados. Assim, neste trabalho, entre outros, um dos objetivos, foi mostrar que o tempo de espera na fila de caixas de supermercados assume grande importância na rapidez de atendimento e, portanto, para o nível de serviço dos clientes. Outros objetivos também foram considerados. As causas pelas quais o cliente freqüenta aquele supermercado e, nestas, a relevância de cada uma em contraste com as outras, e sua importância relativa. Assim, pôde-se contextualizar o cenário no qual os clientes enxergam a importância da fila e de seu tempo de espera. Também, associou-se a escolaridade do cliente a fatores pelos quais este freqüenta o local, sendo esta uma contribuição interessante devido a existir, no Brasil, uma relação entre renda e escolaridade. Também, estudaram-se modelos de filas que podem representar satisfatoriamente o sistema de filas nos caixas de supermercados e identificouse, entre eles, o que melhor representou o sistema. Para o modelo de filas com trocas, foi verificado que os clientes trocam de fila quando percebem outra fila com menos clientes, sendo que o tamanho desta diferença foi avaliado. Este modelo foi o que melhor representou a situação comumente encontrada nos supermercados podendo fornecer subsídios para melhoria de atendimento. Para a viabilização da pesquisa foram contatadas algumas empresas da cidade de São Carlos/SP, sendo que, daquelas que permitiram a coleta de dados, uma foi selecionada. Desta forma, este trabalho se trata de um estudo de caso, tendo limitações inferenciais.

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.

In this thesis, we study the tradeoff of average delay with average service cost and average utility for both continuous time and discrete time single server queueing models without and with admission control. The continuous time and discrete time queueing models that we consider are motivated by cross-layer models for point-to-point links with random packet arrivals and fading at slow and fast time scales. Our studies are motivated by the need to optimally tradeoff the average delay of the packets (a network layer performance measure) with the average service cost of transmitting the packets, e.g. the average power required for transmission (a physical layer performance measure) under a lower bound constraint on the average throughput, in various point-to-point communication scenarios. The tradeoff problems are studied for a class of monotone and stationary scheduling policies and under the assumption that the service cost rate and utility rate are respectively convex and concave functions of the service rate and arrival rate. We also consider the problem of optimally trading off the average delay and average error rate of randomly arriving message symbols which are transmitted over a noisy point-to-point link, in which case the service cost function is non-convex. The solutions to the tradeoff problems that we address in the thesis are asymptotic in nature, and are similar in spirit to the Berry-Gallager asymptotic bounds. It is intuitive that to keep a queue stable under a lower bound constraint on the average utility a minimum number of customers have to be served per unit time. This in turn implies that queue stability requires a minimum average service cost expenditure. In the thesis we obtain an asymptotic characterization of the minimum average delay for monotone stationary policies subject to an upper bound constraint on the average service cost and a lower bound constraint on the average utility, in the asymptotic regime where the average service cost constraint is made arbitrarily close to the above minimum average service cost. In the thesis, we obtain asymptotic lower bounds on the minimum average delay for the cases for which lower bounds were previously not known. The asymptotic characterization of the minimum average delay for monotone stationary policies, for both continuous time and discrete time models, is obtained via geometric bounds on the stationary probability of the queue length, in the above asymptotic regime. The restriction to monotone stationary policies enables us to obtain an intuitive explanation for the behaviour of the asymptotic lower bounds using the above geometric bounds on the stationary probability distribution of the queue length. The geometric bounds on the stationary probability of the queue length also lead to a partial asymptotic characterization of the structure of any optimal monotone stationary policy, in the above asymptotic regime, which was not available in previous work. Furthermore, the geometric bounds on the stationary probability can be extended to analyse the tradeoff problem in other scenarios, such as for other continuous time queueing models, multiple user communication models, queueing models with service time control, and queueing models with general holding costs. Usually, queueing models with integer valued queue evolution, are approximated by queueing models with real valued queue evolution and strictly convex service cost functions for analytical tractability. Using the asymptotic bounds, we show that for some cases the average delay does not grow to infinity in the asymptotic regime, although the approximate model suggests that the average delay does grow to infinity. In other cases where the average delay does grow to infinity in the asymptotic regime, our results illustrate that the tradeoff behaviour of the approximate model is different from that of the original integer valued queueing model unless the service cost function is modelled as the piecewise linear lower convex envelope of the service cost function for the original model.