27 research outputs found

    A generic method to develop simulation models for ambulance systems

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    In this paper, we address the question of generic simulation models and their role in improving emergency care around the world. After reviewing the development of ambulance models and the contexts in which they have been applied, we report the construction of a reusable model for ambulance systems. Further, we describe the associated parameters, data sources, and performance measures, and report on the collection of information, as well as the use of optimisation to configure the service to best effect. Having developed the model, we have validated it using real data from the emergency medical system in a Brazilian city, Belo Horizonte. To illustrate the benefits of standardisation and reusability we apply the model to a UK context by exploring how different rules of engagement would change the performance of the system. Finally, we consider the impact that one might observe if such rules were adopted by the Brazilian system

    Location models in the public sector

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    The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.Location analysis, public facilities, covering models

    Models for ambulance planning on the strategic and the tactical level

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    Ambulance planning involves decisions to be made on different levels. The decision for choosing base locations is usually made for a very long time (strategic level), but the number and location of used ambulances can be changed within a shorter time period (tactical level). We present possible formulations for the planning problems on these two levels and discuss solution approaches that solve both levels either simultaneously or separately. The models are set up such that different types of coverage constraints can be incorporated. Therefore, the models and approaches can be applied to different emergency medical services systems occurring all over the world. The approaches are tested on data based on the situation in the Netherlands and compared based on computation time and solution quality. The results show that the solution approach that solves both levels separately performs better when considering minimizing the number of bases. However, the solution approach that solves both levels simultaneously performs better when considering minimizing the number of ambulances. In addition, with the latter solution approach it is easier to make a good trade-off between minimizing the number of bases and ambulances because it considers a weighted objective function. However, the computation time of this approach increases exponentially with the input size whereas the computation time of the approach that solves both levels separately follows a more linear trend

    AGENT-BASED DISCRETE EVENT SIMULATION MODELING AND EVOLUTIONARY REAL-TIME DECISION MAKING FOR LARGE-SCALE SYSTEMS

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    Computer simulations are routines programmed to imitate detailed system operations. They are utilized to evaluate system performance and/or predict future behaviors under certain settings. In complex cases where system operations cannot be formulated explicitly by analytical models, simulations become the dominant mode of analysis as they can model systems without relying on unrealistic or limiting assumptions and represent actual systems more faithfully. Two main streams exist in current simulation research and practice: discrete event simulation and agent-based simulation. This dissertation facilitates the marriage of the two. By integrating the agent-based modeling concepts into the discrete event simulation framework, we can take advantage of and eliminate the disadvantages of both methods.Although simulation can represent complex systems realistically, it is a descriptive tool without the capability of making decisions. However, it can be complemented by incorporating optimization routines. The most challenging problem is that large-scale simulation models normally take a considerable amount of computer time to execute so that the number of solution evaluations needed by most optimization algorithms is not feasible within a reasonable time frame. This research develops a highly efficient evolutionary simulation-based decision making procedure which can be applied in real-time management situations. It basically divides the entire process time horizon into a series of small time intervals and operates simulation optimization algorithms for those small intervals separately and iteratively. This method improves computational tractability by decomposing long simulation runs; it also enhances system dynamics by incorporating changing information/data as the event unfolds. With respect to simulation optimization, this procedure solves efficient analytical models which can approximate the simulation and guide the search procedure to approach near optimality quickly.The methods of agent-based discrete event simulation modeling and evolutionary simulation-based decision making developed in this dissertation are implemented to solve a set of disaster response planning problems. This research also investigates a unique approach to validating low-probability, high-impact simulation systems based on a concrete example problem. The experimental results demonstrate the feasibility and effectiveness of our model compared to other existing systems

    GESTÃO DE OPERAÇÕES DE SERVIÇO: UMA REVISÃO SISTEMÁTICA SOBRE A PRODUÇÃO NACIONAL

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    O presente estudo tem como objetivo realizar uma revisĂŁo sistemĂĄtica dos artigos publicados em Ăąmbito nacional que abordem o tema GestĂŁo de OperaçÔes em Serviço (GOS), no perĂ­odo de 2004 a 2014, em revistas de alto impacto, classificadas como A1 e A2 no sistema Qualis/Capes na ĂĄrea de Administração. Como no perĂ­odo da pesquisa nĂŁo existiam revistas nacionais classificadas como A1, o estudo focou nos periĂłdicos A2. As informaçÔes analisadas buscaram responder quatro questĂ”es de pesquisa: (A) Que variaçÔes podem ter ocorrido no nĂșmero de publicaçÔes em OperaçÔes de Serviço no decorrer dos anos? (B) Quais sĂŁo os principais temas de pesquisa? (C) Que mĂ©todos sĂŁo usados em pesquisas de GOS? (D) Quais os setores de atividade sĂŁo mais estudados? Os resultados encontrados evidenciaram um destaque para a temĂĄtica de planejamento e uma tendĂȘncia para estudos empĂ­ricos com foco em survey e estudos de caso. Quanto aos setores, a maior atenção dos pesquisadores foi dada a saĂșde, seguido por transporte e saneamento bĂĄsico. Constatou-se tambĂ©m que nĂŁo ocorreu um aumento regular no nĂșmero de artigos sobre GOS ao longo dos anos. Os resultados encontrados foram comparados com estudos anteriores

    GESTÃO DE OPERAÇÕES DE SERVIÇO: UMA REVISÃO SISTEMÁTICA SOBRE A PRODUÇÃO NACIONAL

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    O presente estudo tem como objetivo realizar uma revisĂŁo sistemĂĄtica dos artigos publicados em Ăąmbito nacional que abordem o tema GestĂŁo de OperaçÔes em Serviço (GOS), no perĂ­odo de 2004 a 2014, em revistas de alto impacto, classificadas como A1 e A2 no sistema Qualis/Capes na ĂĄrea de Administração. Como no perĂ­odo da pesquisa nĂŁo existiam revistas nacionais classificadas como A1, o estudo focou nos periĂłdicos A2. As informaçÔes analisadas buscaram responder quatro questĂ”es de pesquisa: (A) Que variaçÔes podem ter ocorrido no nĂșmero de publicaçÔes em OperaçÔes de Serviço no decorrer dos anos? (B) Quais sĂŁo os principais temas de pesquisa? (C) Que mĂ©todos sĂŁo usados em pesquisas de GOS? (D) Quais os setores de atividade sĂŁo mais estudados? Os resultados encontrados evidenciaram um destaque para a temĂĄtica de planejamento e uma tendĂȘncia para estudos empĂ­ricos com foco em survey e estudos de caso. Quanto aos setores, a maior atenção dos pesquisadores foi dada a saĂșde, seguido por transporte e saneamento bĂĄsico. Constatou-se tambĂ©m que nĂŁo ocorreu um aumento regular no nĂșmero de artigos sobre GOS ao longo dos anos. Os resultados encontrados foram comparados com estudos anteriores

    Modeling Lane-based Traffic Flow In Emergency Situations In The Presence Of Multiple Heterogeneous Flows

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    In recent years, natural, man-made and technological disasters have been increasing in magnitude and frequency of occurrence. Terrorist attacks have increased after the September 11, 2001. Some authorities suggest that global warming is partly the blame for the increase in frequency of natural disasters, such as the series of hurricanes in the early-2000\u27s. Furthermore, there has been noticeable growth in population within many metropolitan areas not only in the US but also worldwide. These and other facts motivate the need for better emergency evacuation route planning (EERP) approaches in order to minimize the loss of human lives and property. This research considers aspects of evacuation routing never before considered in research and, more importantly, in practice. Previous EERP models only either consider unidirectional evacuee flow from the source of a hazard to destinations of safety or unidirectional emergency first responder flow to the hazard source. However, in real-life emergency situations, these heterogeneous, incompatible flows occur simultaneously over a bi-directional capacitated lane-based travel network, especially in unanticipated emergencies. By incompatible, it is meant that the two different flows cannot occupy a given lane and merge or crossing point in the travel network at the same time. In addition, in large-scale evacuations, travel lane normal flow directions can be reversed dynamically to their contraflow directions depending upon the degree of the emergency. These characteristics provide the basis for this investigation. This research considers the multiple flow EERP problem where the network travel lanes can be reconfigured using contraflow lane reversals. The first flow is vehicular flow of evacuees from the source of a hazard to destinations of safety, and the second flow is the emergency first responders to the hazard source. After presenting a review of the work related to the multiple flow EERP problem, mathematical formulations are proposed for three variations of the EERP problem where the objective for each problem is to identify an evacuation plan (i.e., a flow schedule and network contraflow lane configuration) that minimizes network clearance time. Before the proposed formulations, the evacuation problem that considers only the flow of evacuees out of the network, which is viewed as a maximum flow problem, is formulated as an integer linear program. Then, the first proposed model formulation, which addresses the problem that considers the flow of evacuees under contraflow conditions, is presented. Next, the proposed formulation is expanded to consider the flow of evacuees and responders through the network but under normal flow conditions. Lastly, the two-flow problem of evacuees and responders under contraflow conditions is formulated. Using real-world population and travel network data, the EERP problems are each solved to optimality; however, the time required to solve the problems increases exponentially as the problem grows in size and complexity. Due to the intractable nature of the problems as the size of the network increases, a genetic-based heuristic solution procedure that generates evacuation network configurations of reasonable quality is proposed. The proposed heuristic solution approach generates evacuation plans in the order of minutes, which is desirable in emergency situations and needed to allow for immediate evacuation routing plan dissemination and implementation in the targeted areas

    OR models in urban service facility location : a critical review of applications and future developments

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    [EN] Facility location models are well established in various application areas with more than a century of history in academia. Since the 1970s the trend has been shifting from manufacturing to service industries. Due to their nature, service industries are frequently located in or near urban areas that results in additional assumptions, objectives and constraints other than those in more traditional manufacturing location models. This survey focuses on the location of service facilities in urban areas. We studied 110 research papers across different journals and disciplines. We have analyzed these papers on two levels. On the first, we take an Operations Research perspective to investigate the papers in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. On the second level, we compare and contrast the papers in each of these applications categories: (a) Waste management systems (WMS), (b) Large-scale disaster (LSD), (c) Small-scale emergency (SSE), (d) General service and infrastructure (GSI), (e) Non-emergency healthcare systems (NEH) and (f) Transportation systems and their infrastructure (TSI). Each of these categories is critically analyzed in terms of application, assumptions, decision variables, input parameters, constraints, objective functions and solution techniques. Gaps, research opportunities and trends are identified within each category. Finally, some general lessons learned based on the practicality of the models is synthesized to suggest avenues of future research.Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards (No. DPI2015-65895-R) financed by FEDER funds.Farahani, RZ.; Fallah, S.; Ruiz GarcĂ­a, R.; Hosseini, S.; Asgari, N. (2019). OR Models in Urban Service Facility Location: A Critical Review of Applications and Future Developments. European Journal of Operational Research. 276(1):1-27. https://doi.org/10.1016/j.ejor.2018.07.036S127276
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