An integrated approach for strategic and tactical decisions for the emergency medical service: Exploring optimization and metamodel-based simulation for vehicle location

Amorim, Marco; Antunes, Francisco; Ferreira, Sara; Couto, António

doi:10.1016/j.cie.2019.106057

Cited by 26 publications

(13 citation statements)

References 38 publications

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“…Our method manages to georeference 75% of entities in a range of 0 to 25 km and 50% within less than 5 km. In real-time applications, this type of result can be highly relevant; for example, for linking emergency medical systems [34], event detection on social media [12], and place detection in location-based services [35], among others.…”

Section: Discussionmentioning

confidence: 99%

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text

et al. 2020

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The automatic extraction of geospatial information is an important aspect of data mining. Computer systems capable of discovering geographic information from natural language involve a complex process called geoparsing, which includes two important tasks: geographic entity recognition and toponym resolution. The first task could be approached through a machine learning approach, in which case a model is trained to recognize a sequence of characters (words) corresponding to geographic entities. The second task consists of assigning such entities to their most likely coordinates. Frequently, the latter process involves solving referential ambiguities. In this paper, we propose an extensible geoparsing approach including geographic entity recognition based on a neural network model and disambiguation based on what we have called dynamic context disambiguation. Once place names are recognized in an input text, they are solved using a grammar, in which a set of rules specifies how ambiguities could be solved, in a similar way to that which a person would utilize, considering the context. As a result, we have an assignment of the most likely geographic properties of the recognized places. We propose an assessment measure based on a ranking of closeness relative to the predicted and actual locations of a place name. Regarding this measure, our method outperforms OpenStreetMap Nominatim. We include other assessment measures to assess the recognition ability of place names and the prediction of what we called geographic levels (administrative jurisdiction of places).

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Section: Discussionmentioning

confidence: 99%

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text

et al. 2020

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“…Coelho and Pinto, 25 Amorim et al, 54 and Antunes et al 56 based their location decision on a predefined potential base location, while Snyder and Smucker 55 optimized the ambulance base location of St. Louis County, Minnesota in a continuous region. They developed a discrete-event simulation (DES) simulation model and then used it to build four types of random forest metamodels with increasing complexity (i.e., 1, 2, 5, and 12 bases).…”

Section: Sbm Applications In Healthcarementioning

confidence: 99%

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

Sahlaoui,

Aboueljinane,

Lebbar

2023

SIMULATION

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Simulation-based metamodels or surrogate models are simplified models that capture the relationship between inputs and outputs of the simulation model. The analytical expression of metamodels is defined using a sample of input/output points obtained from the simulation model. This analytical expression is then embedded in an optimization process that usually provides solutions much faster than other simulation-based optimization techniques such as metaheuristics or mathematical modeling. The goal of this paper is to describe the simulation-based metamodeling approach and to provide a thorough review of the literature on its applications to emergency healthcare systems. For this purpose, we examine the recent literature (journals and conference proceedings) published in the last 15 years (2008–2022). Finally, we identify findings and avenues of research in simulation-based metamodeling that deserve special attention from the scientific community and allow the potential of this approach to be used for better decision-making in emergency healthcare.

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“…Most scholars have classified the problems of regional public facility location models into four types: the P-median problem, P-center problem, location set covering problem (LSCP) and maximal covering location problem (MCLP). Owing to the increasing complexity of the social environment and the evaluation factors of each facility site selection, different site selection models and theories have emerged to solve various facility site selection problems (Basar et al ., 2011; Beraldi and Bruni, 2009; Blanquero et al ., 2016; Liu, 2016; Amorim et al ., 2019). During the planning stage, planners must seek appropriate models and theories to explore and analyze facilities according to their attributes and characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Location optimization of emergency medical facilities for public health emergencies in megacities based on genetic algorithm

Liu

et al. 2022

ECAM

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PurposeThe purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.Design/methodology/approachUsing Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.FindingsComparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.Research limitations/implicationsFirst, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.Practical implicationsThe results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.Social implicationsThe results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.Originality/valueThe research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

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An integrated approach for strategic and tactical decisions for the emergency medical service: Exploring optimization and metamodel-based simulation for vehicle location

Cited by 26 publications

References 38 publications

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

Location optimization of emergency medical facilities for public health emergencies in megacities based on genetic algorithm

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