Otimização da configuração e operação de sistemas médicos emergenciais em rodovias utilizando o modelo hipercubo.

The purpose of this study is to develop effective methods to analyze the configuration and operation of the emergency medical systems (EMS) on highways. Due to the stochastic nature of these systems, especially in the arrival and assistance processes of the emergency calls, we apply the Hypercube Queuing Model to evaluate the performance measures of the system. This is a well-known model in the location literature, which is based on spatially distributed queuing theory. The EMS on highways operate within a particular dispatching policy which considers that only some ambulances in the system can travel to certain regions (partial backup) and multiple dispatch of ambulances to respond to certain calls. In this study we extend the Hypercube model to deal with these situations. Since the Hypercube model is a descriptive model, we also develop a Hypercube embedded genetic algorithm to create a prescriptive approach to optimize the configuration and operation of EMS on highways. This approach can support decisions at the strategic level, for example, the location of ambulances along the highway and the primary response area to each ambulance, as well as, decisions on the operational level, for example, the optimal dispatch policy of ambulances to respond to the emergency calls and the coverage area to each ambulance (if the system configuration can be modified according to the operational conditions of the week or the day). In order to evaluate the performance of the proposed approach, we conducted experiments using the data of two realsystems: the EMS Anjos do Asfalto (Presidente Dutra highway) and EMS Centrovias (portions of the highways Washington Luis, Eng. Paulo Nilo Romano e Comandante João Ribeiro de Barros) in São Paulo State. The results show that the approach is effective to support planning and operation decisions in such systems.Financiadora de Estudos e ProjetosO objetivo deste trabalho é desenvolver métodos efetivos para analisar a configuração e operação de sistemas de atendimento emergencial (SAEs) em rodovias. Devido às características estocásticas de tais sistemas, principalmente nos processos de chegada e atendimento dos chamados de emergência, aplicamos o modelo Hipercubo para analisar as medidas de desempenho do sistema. Este modelo, conhecido na literatura de localização de sistemas de emergência, é baseado em teoria de filas espacialmente distribuídas. Os SAEs em rodovia operam com uma política de despacho particular, a qual admite que apenas algumas ambulâncias do sistema possam viajar a determinadas regiões (backup parcial) e utiliza múltiplo despacho de ambulâncias para atender a certas chamadas. Neste trabalho estendemos o modelo Hipercubo para analisar tais situações. Como o modelo Hipercubo é descritivo, combinamos estas extensões do modelo Hipercubo com um algoritmo genético para obter uma abordagem prescritiva capaz de otimizar a configuração e operação de SAEs em rodovias. Tal abordagem pode ser útil para apoiar decisões no plano estratégico, por exemplo, a localização das bases das ambulâncias ao longo da rodovia e o dimensionamento das regiões de cobertura de cada base. Assim como apoiar decisões no plano operacional, por exemplo, a escolha da política de despacho das ambulâncias para atender chamados de urgência e a determinação das áreas de cobertura de cada servidor (quando a configuração do sistema puder ser alterada de acordo com as condições operacionais de uma semana ou de um dia). Para analisar o desempenho desta abordagem, realizamos estudos de casos com dados reais do sistema Anjos do Asfalto (rodovia Presidente Dutra) e da concessionária Centrovias (trechos das rodovias Washington Luis, Eng. Paulo Nilo Romano e Comandante João Ribeiro de Barros), no interior de São Paulo. Os resultados mostram que a abordagem é efetiva para apoiar decisões relacionadas ao planejamento e operação destes sistemas

A discrete simulation analysis of a logistics supply system

An important aspect of logistics supply systems in agro industries is to manage the processes of harvesting and transporting raw materials, from the rural fields to the processing plants. The truck waiting times in the various queues of the plant reception area are of particular concern. This paper applies discrete simulation techniques to study the reception area processes of a sugarcane plant, analyzing the performance of the system and investigating alternative configurations and policies for its operations. The analysis is also useful for other agro industries with similar supply systems, such as orange and wood industries.Discrete simulation Logistics supply system Agro industries Sugarcane

An optimization approach for ambulance location and the districting of the response segments on highways

In this paper we present a method to optimize the configuration and operation of emergency medical systems on highways. Different from the approaches studied in the previous papers, the present method can support two combined configuration decisions: the location of ambulance bases along the highway and the districting of the response segments. For example, this method can be used to make decisions regarding the optimal location and coverage areas of ambulances in order to minimize mean user response time or remedy an imbalance in ambulance workloads within the system. The approach is based on embedding a well-known spatially distributed queueing model (hypercube model) into a hybrid genetic algorithm to optimize the decisions involved. To illustrate the application of the proposed method, we utilize two case studies on Brazilian highways and validate the findings via a discrete event simulation model.Location and dispatching of ambulances Hypercube model Genetic algorithm Spatially distributed queues Highways

Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model

In this study, we present a series of well-known optimization methods to address two related decisions associated with the design of large-scale ambulance operations on highways: (1) The question of location, and (2) the issue of districting. As a result of computer storage and runtime constraints, previous approaches have only considered small-to-moderate scale problem scenarios, generally employing exact hypercube queuing models integrated into optimization procedures. We overcome these limitations here by embedding a fast and accurate hypercube approximation algorithm adapted for partial backup dispatch policies in single- and multi-start greedy heuristics. The proposed methods are tested on small-to-large-scale problems involving up to 100 ambulances. The results suggest that our approach is a viable alternative for the analysis and configuration of large-scale highway emergency medical systems, providing reasonable accuracy and affordable run times.Emergency medical systems Ambulance deployment Approximate hypercube queuing model Multi-start greedy heuristic Probabilistic location and districting problems

Análise da configuração de SAMU utilizando múltiplas alternativas de localização de ambulâncias Analysis of SAMU configuration using multiple alternatives of ambulance location

O Sistema de Atendimento Móvel de Urgência (SAMU) no Brasil é um sistema médico emergencial de responsabilidade do poder público, em que a demanda de usuários em uma região urbana é usualmente separada por subregiões e classes de chamados emergenciais. Essa demanda pode mudar de forma significativa ao longo do dia, geograficamente e temporalmente, devido à sua natureza aleatória, mas também devido aos diferentes padrões de comportamentos da população ao longo do dia. Por exemplo, tipicamente há menos demanda durante a noite do que de dia. Os objetivos deste trabalho são: verificar se o conhecido modelo hipercubo de filas espacialmente distribuídas é adequado para analisar medidas de desempenho do SAMU, tais como tempos médios de resposta aos usuários, e utilizar este modelo para analisar múltiplas alternativas de localização das ambulâncias, explorando variações importantes da demanda e do serviço ao longo do dia. Para verificar a viabilidade e a aplicabilidade desta abordagem, foi realizado um estudo de caso no SAMU de Ribeirão Preto-SP.<br>The Brazilian emergency medical system SAMU (Sistema de Atendimento Móvel de Urgência) is an emergency medical system of public government liability, in which the users' service demand in an urban region is usually separated into subregions and classes of emergency calls. This demand can change substantially during the day, geographically and temporally, due to its random nature and also to the different behavior patterns of the population throughout the day. For instance, typically there is less demand during the night hours than during the day. The goals of this study are to verify whether the hypercube queuing model is adequate to analyze performance measures of SAMU, such as mean response times to the users, and use this model to analyze multiple alternatives of ambulance location considering significant variations in the demand and service throughout the day. In order to verify the feasibility and applicability of this approach, a case study was conducted in the SAMU of Ribeirão Preto-SP

Towards hypercube queuing models for dispatch policies with priority in queue and partial backup

International audienc

Incorporating priorities for waiting customers in the hypercube queuing model with application to an emergency medical service system in Brazil

Emergency medical services (EMS) assist different classes of patients according to their medical seriousness. In this study, we extended the well-known hypercube model, based on the theory of spatially distributed queues, to analyze systems with multiple priority classes and a queue for waiting customers. Then, we analyzed the computational results obtained when applying this approach to a case study from an urban EMS in the city of Ribeirao Preto, Brazil. We also investigated some scenarios for this system studying different periods of the day and the impact of increasing the demands of the patient classes. The results showed that relevant performance measures can be obtained to analyze such a system by using the analytical model extended to deal with queuing priority. In particular, it can accurately evaluate the average response time for each class of emergency calls individually, paying particular attention to high priority calls. (C) 2014 Elsevier B.V. All rights reserved.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP