135 research outputs found

    Developing service supply chains by using agent based simulation

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    The Master thesis present a novel approach to model a service supply chain with agent based simulation. Also, the case study of thesis is related to healthcare services and research problem includes facility location of healthcare centers in Vaasa region by considering the demand, resource units and service quality. Geographical information system is utilized for locating population, agent based simulation for patients and their illness status probability, and discrete event simulation for healthcare services modelling. Health centers are located on predefined sites based on managers’ preference, then each patient based on the distance to health centers, move to the nearest point for receiving the healthcare services. For evaluating cost and services condition, various key performance indicators have defined in the modelling such as Number of patient in queue, patients waiting time, resource utilization, and number of patients ratio yielded by different of inflow and outflow. Healthcare managers would be able to experiment different scenarios based on changing number of resource units or location of healthcare centers, and subsequently evaluate the results without necessity of implementation in real life.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

    Lean enterprise distribution tactics with customer supply chain integrations

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    Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2003.Includes bibliographical references (p. 108-118).by Eric A. White.S.M.M.B.A

    Dynamic Pricing in Heterogeneous Wireless Cellular Networks

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    Smart communications devices are giving users instant access to applications that consume large amounts of data. These applications have different requirements on the network for delivery of data. In order to support these different applications, operators are required to support multiple service classes. Given the regulatory and technology constraints and the relatively high cost associated with wireless spectrum licensing and utilization, demand will exceed supply leading to congestion and overload conditions. In addition to new broadband radio technologies offering higher data rates, operators are looking at deploying alternate heterogeneous technologies, such as WLAN, to provide additional bandwidth for serving customers. It is expected that this will still fall short of providing enough network resources to meet the ITU requirement for 1% new call blocking probability. An economic mechanism that offers incentives to individuals for rational behavior is required in order in order to reduce the demand for network resources and resolve the congestion problem. The research in this dissertation demonstrates that the integration of a dynamic pricing with connection admission control mechanism for an operator deploying cooperative heterogeneous networks (e.g., LTE and WLAN) offering multiple QoS service classes reduces the new call blocking probability to the required 1% level. The experimental design consisted, first, of an analytical model of the CAC algorithm with dynamic pricing in a heterogeneous environment. The analytical model was subsequently validated through discrete-event simulation using Matlab

    Impact of Mobility and Wireless Channel on the Performance of Wireless Networks

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    This thesis studies the impact of mobility and wireless channel characteristics, i. e. , variability and high bit-error-rate, on the performance of integrated voice and data wireless systems from network, transport protocol and application perspectives. From the network perspective, we study the impact of user mobility on radio resource allocation. The goal is to design resource allocation mechanisms that provide seamless mobility for voice calls while being fair to data calls. In particular, we develop a distributed admission control for a general integrated voice and data wireless system. We model the number of active calls in a cell of the network as a Gaussian process with time-dependent mean and variance. The Gaussian model is updated periodically using the information obtained from neighboring cells about their load conditions. We show that the proposed scheme guarantees a prespecified dropping probability for voice calls while being fair to data calls. Furthermore, the scheme is stable, insensitive to user mobility process and robust to load variations. From the transport protocol perspective, we study the impact of wireless channel variations and rate scheduling on the performance of elastic data traffic carried by TCP. We explore cross-layer optimization of the rate adaptation feature of cellular networks to optimize TCP throughput. We propose a TCP-aware scheduler that switches between two rates as a function of TCP sending rate. We develop a fluid model of the steady-state TCP behavior for such a system and derive analytical expressions for TCP throughput that explicitly account for rate variability as well as the dependency between the scheduler and TCP. The model is used to choose RF layer parameters that, in conjunction with the TCP-aware scheduler, improve long-term TCP throughput in wireless networks. A distinctive feature of our model is its ability to capture variability of round-trip-time, channel rate and packet error probability inherent to wireless communications. From the application perspective, we study the performance of wireless messaging systems. Two popular wireless applications, the short messaging service and multimedia messaging service are considered. We develop a mathematical model to evaluate the performance of these systems taking into consideration the fact that each message tolerates only a limited amount of waiting time in the system. Using the model, closed-form expressions for critical performance parameters such as message loss, message delay and expiry probability are derived. Furthermore, a simple algorithm is presented to find the optimal temporary storage size that minimizes message delay for a given set of system parameters
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