830 resultados para discrete event systems
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Pós-graduação em Engenharia Elétrica - FEIS
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Cost-effectiveness and budget impact of saxagliptine as additional therapy to metformin for the treatment of diabetes mellitus type 2 in the Brazilian private health system Objectives: To compare costs and clinical benefits of three additional therapies to metformin (MF) for patients with diabetes mellitus type 2 (DM2). Methods: A discrete event simulation model seas built to estimate the cost-utility ratio (cost per quality-adjusted life years [QALY)) of saxagliptine as an additional therapy to MF when compared to rosiglitazone or pioglitazone. A budget impact model (BIM) was built to simulate the economic impact of saxagliptine use in the context of the Brazilian private health system. Results: The acquiring medication costs for the hypothetical patient group analyzed in a time frame of three years, were R$ 10,850,185, R$ 14,836,265 and R$ 14,679,099 for saxagliptine, pioglitazone and rosiglitazone, respectively. Saxagliptine showed lower costs and greater effectiveness in both comparisons, with projected savings for the first three years of R$ 3,874 and R$ 3,996, respectively. The BIM estimated cumulative savings of R$ 417,958 with the repayment of saxagliptine in three years from the perspective of a health plan with 1,000,000 covered individuals. Conclusion: From the perspective of private paying source, the projection is that adding saxagliptine with MF save costs when compared with the addition of rosiglitazone or pioglitazone in patients with DM2 that have not reached the HbA1c goal with metformin monotherapy. The BIM of including saxagliptine in the reimbursement lists of health plans indicated significant savings on the three-year horizon.
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This paper presents the results of a simulation using physical objects. This concept integrates the physical dimensions of an entity such as length, width, and weight, with the usual process flow paradigm, recurrent in the discrete event simulation models. Based on a naval logistics system, we applied this technique in an access channel of the largest port of Latin America. This system is composed by vessel movement constrained by the access channel dimensions. Vessel length and width dictates whether it is safe or not to have one or two ships simultaneously. The success delivered by the methodology proposed was an accurate validation of the model, approximately 0.45% of deviation, when compared to real data. Additionally, the model supported the design of new terminals operations for Santos, delivering KPIs such as: canal utilization, queue time, berth utilization, and throughput capability
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In this thesis we focus on optimization and simulation techniques applied to solve strategic, tactical and operational problems rising in the healthcare sector. At first we present three applications to Emilia-Romagna Public Health System (SSR) developed in collaboration with Agenzia Sanitaria e Sociale dell'Emilia-Romagna (ASSR), a regional center for innovation and improvement in health. Agenzia launched a strategic campaign aimed at introducing Operations Research techniques as decision making tools to support technological and organizational innovations. The three applications focus on forecast and fund allocation of medical specialty positions, breast screening program extension and operating theater planning. The case studies exploit the potential of combinatorial optimization, discrete event simulation and system dynamics techniques to solve resource constrained problem arising within Emilia-Romagna territory. We then present an application in collaboration with Dipartimento di Epidemiologia del Lazio that focuses on population demand of service allocation to regional emergency departments. Finally, a simulation-optimization approach, developed in collaboration with INESC TECH center of Porto, to evaluate matching policies for the kidney exchange problem is discussed.
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Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.
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The present research is based on the notion that disengagement from goals is not a discrete event but a process (Klinger, 1975). A critical phase in this process is when difficulties and setbacks in striving for a goal accumulate. This critical phase is termed here as an action crisis. Given the profound effects that people's thoughts have on their self-regulatory efficiency, it is essential to understand the cognitive correlates of an action crisis. In two experimental lab and two correlational field studies, the hypothesis that goal-related costs and benefits become cognitively highly accessible during an action crisis was tested and supported. Participants who were experiencing an action crisis in such diverse goal areas as intimate relationships, sports, and university studies, thought about goal-related costs and benefits more intensively and frequently in comparison to participants who were not in an action crisis. In an incidental learning task they recognized more of cost–benefit-items and less of implementation-items than the control group. Results are interpreted in terms of action phase specific mindsets (Gollwitzer, 1990, 2012).
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A critical phase in goal striving occurs when setbacks accumulate and goal disengagement becomes an issue. This critical phase is conceptualized as an action crisis and assumed to be characterized by an intrapsychic conflict in which the individual becomes torn between further goal pursuit and goal disengagement. Our theorizing converges with Klinger’s conceptualization of goal disengagement as a process, rather than a discrete event. Two longitudinal field studies tested and found support for the hypothesis that an action crisis not only compromises an individual’s psychological and physiological well-being, but also dampens the cognitive evaluation of the respective goal. In Study 3, marathon runners experiencing an action crisis in their goal of running marathons showed a stronger cortisol secretion and a lower performance in the race 2 weeks later. Results are interpreted in terms of action-phase–specific mindsets with a focus on self-regulatory processes in goal disengagement.
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The Phase I clinical trial is considered the "first in human" study in medical research to examine the toxicity of a new agent. It determines the maximum tolerable dose (MTD) of a new agent, i.e., the highest dose in which toxicity is still acceptable. Several phase I clinical trial designs have been proposed in the past 30 years. The well known standard method, so called the 3+3 design, is widely accepted by clinicians since it is the easiest to implement and it does not need a statistical calculation. Continual reassessment method (CRM), a design uses Bayesian method, has been rising in popularity in the last two decades. Several variants of the CRM design have also been suggested in numerous statistical literatures. Rolling six is a new method introduced in pediatric oncology in 2008, which claims to shorten the trial duration as compared to the 3+3 design. The goal of the present research was to simulate clinical trials and compare these phase I clinical trial designs. Patient population was created by discrete event simulation (DES) method. The characteristics of the patients were generated by several distributions with the parameters derived from a historical phase I clinical trial data review. Patients were then selected and enrolled in clinical trials, each of which uses the 3+3 design, the rolling six, or the CRM design. Five scenarios of dose-toxicity relationship were used to compare the performance of the phase I clinical trial designs. One thousand trials were simulated per phase I clinical trial design per dose-toxicity scenario. The results showed the rolling six design was not superior to the 3+3 design in terms of trial duration. The time to trial completion was comparable between the rolling six and the 3+3 design. However, they both shorten the duration as compared to the two CRM designs. Both CRMs were superior to the 3+3 design and the rolling six in accuracy of MTD estimation. The 3+3 design and rolling six tended to assign more patients to undesired lower dose levels. The toxicities were slightly greater in the CRMs.^
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Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.
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Action systems are a framework for reasoning about discrete reactive systems. Back, Petre and Porres have extended these action systems to continuous action systems, which can be. used to model hybrid systems. In this paper we define a refinement relation, and develop practical data refinement rules for continuous action systems. The meaning of continuous action systems is expressed in terms of a mapping from continuous action systems to action systems. First, we present a new mapping from continuous act ion systems to action systems, such that Back's definition of trace refinement is correct with respect to it. Second, we present a stream semantics that is compatible with the trace semantics, but is preferable to it because it is more general. Although action system trace refinement rules are applicable to continuous action systems with a stream semantics, they are not complete. Finally, we introduce a new data refinement rule that is valid with respect to the stream semantics and can be used to prove refinements that are not possible in the trace semantics, and we analyse the completeness of our new rule in conjunction with the existing trace refinement rules.
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A discrete event simulation model was developed and used to estimate the storage area required for a proposed overseas textile manufacturing facility. It was found that the simulation was able to achieve this because of its ability to both store attribute values and to show queuing levels at an individual product level. It was also found that the process of undertaking the simulation project initiated useful discussions regarding the operation of the facility. Discrete event simulation is shown to be much more than an exercise in quantitative analysis of results and an important task of the simulation project manager is to initiate a debate among decision makers regarding the assumptions of how the system operates.
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Presents a simulation study of the costing of police custody operations at a UK police force. The custody operation incorporates the arrest, booking-in, interview, detention and court appearance activities. The Activity Based Costing (ABC) approach is used as a framework to show how costs are generated by the three “drivers” of cost, activity and resource. These relate to the design efficiency of the process, the timing and mix of demand on the process and the cost of resources used to undertake the process respectively. The use of discrete-event simulation allows the incorporation of dynamic (time-dependent) and stochastic (variability) elements in the cost analysis. This enables both the amount and timing of the use of capacity and the generation of cost to be established. The concept of committed and flexible resources directs management decisions to the redeployment of unused capacity or alternatively the identification of additional capacity requirements.
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Suggests that simulation of the workflow component of a computer supported co-operative work (CSCW) system has the potential to reduce the costs of system implementation, while at the same time improving the quality of the delivered system. Demonstrates the value of being able to assess the frequency and volume of workflow transactions using a case study of CSCW software developed for estate agency co-workers in which a model was produced based on a discrete-event simulation approach with implementation on a spreadsheet platform.