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Markov decision process applied to the control of hospital elective admissions

OBJECTIVE To present a decision model for elective (non-emergency) patient admissions control for distinct specialties on a periodic basis. The purpose of controlling patient admissions is to promote a more efficient utilization of hospital resources, thereby preventing idleness or excessive use of these resources, while considering their relative importance. METHODS The patient admission control is modeled as a Markov decision process. A hypothetical prototype is implemented, applying the value iteration algorithm. RESULTS The model is able to generate an optimal admission control policy that maintains resource consumption close to the desired levels of utilization, while optimizing the established deviation costs. CONCLUSION This is a complex model due to its stochastic dynamic and dimensionality. The model has great potential for application, and requires the development of customized solution methods.

Performance evaluation based on system modeling using Statecharts extensions

Abstract This paper presents two extensions for Statecharts: the Stochastic Statecharts, which use the original statecharts notation with a minor modification in the formal semantics and the Queuing Statecharts, which do not follow the pure Statecharts notation, but a join between Statecharts and queuing network representations. Some basic elements of Statecharts are redefined such as events and conditions, besides some concepts referring to the dynamic system behavior. The specification approaches show the basic behavior of a generic queuing system by means of templates and standard events. It is presented the PerformCharts, a new simulation environment based on Statecharts specification, which allows model solution using either Markov chains or the Network Simulator (NS).

Introducing probabilities in Statecharts to specify reactive systems for performance analysis

Statecharts are expressed in a graphical language to specify complex reactive systems. They are extension of state-transition diagrams to which notions of hierarchy and orthogonality have been added. Recently, they have been suggested to represent performance models and in this regard a software package has been developed. In these performance models, the behavior of a system under study is considered to be probabilistic. Therefore, the inclusion of probabilities in Statecharts formalism will be studied. The proposed extension considers that a modeled system reacts probabilistically to events. In order to deal with these models, an analytical computational method based on constructing a Continuous-Time Markov Chain that is equivalent to the Statecharts model is proposed. The aspect of generating a Continuous-Time Markov Chain from Statecharts representation along with the solution to include probabilities among the transitions will be covered in this paper.

QUÃO ACURADAS SÃO AS PROJEÇÕES FINANCEIRAS E ATUARIAIS DO REGIME GERAL DA PREVIDÊNCIA SOCIAL

O presente artigo procura aferir o grau de confiabilidade das previsoes fiscais e atuariais de deficit no Regime Geral de Previdencia Social (RGPS) realizadas pelo governo federal, comparando os dados da Lei de Diretrizes Orcamentarias dos anos de 2002 a 2015 com os resultados efetivamente realizados nas estatisticas oficiais. A pesquisa constata erros de elevada magnitude entre os valores previstos e realizados para a receita, despesa e deficit do sistema previdenciario, para a maioria dos anos, tornando as previsoes realizadas sem qualquer significado. A investigacao sobre as causas dos erros das projecoes levaram a conclusao de que o modelo atuarial do governo federal apoia-se em metodologia impotente para produzir resultados confiaveis. As razoes detectadas vao desde o congelamento, nos valores do ano de 2009, das variaveis do mercado de trabalho ao longo de quatro decadas, ate a inusitada taxa de reajuste do salario minimo acima do PIB e da inflacao. O artigo conclui que o modelo atuarial que pautou a proposta de reforma da previdencia de 2016 foi desenhado para subestimar receitas e superestimar gastos com beneficios, pois esta apoiado em metodo que, apesar de simular infalibilidade, apresenta lacunas logicas. Palavras-chave: Seguridade Social. Modelo atuarial. Reforma da Previdencia

Pontes conceituais entre matemática e redução de risco de desastres socioambientais - o conceito de bacia hidrográfica estocástica

A bacia hidrografica e a unidade espacial basica em estudos hidrologicos. A modelagem deste objeto geografico e de fundamental interesse para reducao de risco de desastres socioambientais. Neste artigo sao apresentados resultados da delimitacao de bacias hidrograficas em uma perspectiva diferente da tradicional, proporcionando recursos de analise inovadores a modelagem de cenarios de risco hidrologico. Trata-se da exploracao do comportamento probabilistico da direcao de escoamento superficial e da analise do efeito que uma pequena alteracao local pode ter na estrutura geral das bacias. Palavras-chave : Desastres Socioambientais. Bacia Hidrografica. Matematica Aplicada. Processos Estocasticos. Mapas de Probabilidades.

Financial forecasts accuracy in Brazil’s social security system

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.

A Markovian sensibility analysis for parallel processing scheduling on GNU/Linux

Parallel Computing has become a powerful tool to overcome certain types of computational problems in many areas such as engineering, especially due to the increasing diversity of platforms for execution of this type of application. The use of parallel computing over LANs and WANs is an alternative in the universe of dedicated environments (parallel machines and clusters), but, in some cases, it needs to imply QoS (Quality of Service) parameters, so it can execute efficiently. In this scenario, the deployment of resource allocation scheme plays an important role in order to satisfy the QoS requirements for parallel applications. In this paper we propose and present Markovian models for resource allocation (CPU allocation) schemes in a GPOS (General Purpose Operating Systems), aiming at offering an optimization method which makes the efficient performance of parallel and interactive applications feasible.

UM MODELO MARKOVIANO DE DECISÃO PARA A OTIMIZAÇÃO DE UM SISTEMA DE MANUTENÇÃO COM TEMPOS DE REPARO COXIANOS E FASES NÃO OBSERVÁVEIS

In this paper we analyse a manufacturing system with two different servers. The times to failure follow an exponential distribution and the machines repair times follow a phase type distribution with Cox configuration. We consider two models: a full information model and a partial information model, which differ themselves by the possibility of observing or not the phases of the phase type distribution. The first one is modelled by a continuous time Markov decision process, and the second one by a decision Markov processes with partial information, as defined in Hordijk & Loeve (1994). Numerical results are presented