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Determination of server location in emergency care systems: an index proposal using data envelopment analysis and the hypercube queuing model.
Mariano, Enzo Barberio; Siqueira, Regiane Máximo; Beojone, Caio Vitor; Luiz, Octaviano Rojas; Luiz, João Victor Rojas; Dos Santos, Hugo Henrique.
Affiliation
  • Mariano EB; Department of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
  • Siqueira RM; Department of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
  • Beojone CV; Urban Transport Systems Laboratory (LUTS), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Luiz OR; Department of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
  • Luiz JVR; Department of Engineering, Institute of Sciences and Engineering, São Paulo State University (Unesp), Itapeva, São Paulo, Brazil.
  • Dos Santos HH; Department of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
PeerJ Comput Sci ; 9: e1637, 2023.
Article in En | MEDLINE | ID: mdl-38077527
The objective of this article is to propose a new composite index (CI) that helps to determine the most effective location of servers in an Emergency Care System (ECS), using Benefit of the Doubt (BoD)/Data Envelopment Analysis (DEA) and the Hypercube queuing model. The CI proposed was developed in four stages: (1) definition of a number of possible ECS configurations through the application of mathematical partitions and permutations; (2) application of the hypercube queuing model to determine performance parameters for each ECS configuration; (3) application of DEA/BoD to build the CI and generate performance rankings, and (4) evaluation of the rankings obtained to define the best configuration for the ECS analyzed. Data from two real cases from Brazil were used to assess the CI proposal. The results obtained confirm that: (a) the hypercube model could, relatively quickly, determine the configuration parameters generated; (b) the application of an appropriate DEA/BoD model enabled the different configurations to be ranked with good discrimination; (c) a pattern in the relationship between ambulance concentration and configuration effectiveness could be identified; and (d) the CI proposed would benefit ECS managers who are making resource location decisions.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: PeerJ Comput Sci Year: 2023 Document type: Article Affiliation country: Brazil Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: PeerJ Comput Sci Year: 2023 Document type: Article Affiliation country: Brazil Country of publication: United States