Iterative optimization algorithm with parameter estimation for the ambulance location problem.
The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This pape...
| Publicado en: | Health Care Management Science Vol. 19; no. 4; pp. 362 - 383 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=119026881&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 119026881 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13869620 BSE jtl: Health Care Management Science issn: 13869620 maglogo: N pubinfo: dt: Dec2016 vid: 19 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 119026881 119026881 NLM26143594 10.1007/s10729-015-9332-4 NLM26143594 119026881 ppf: 362 ppct: 21 formats: tig: atl: Iterative optimization algorithm with parameter estimation for the ambulance location problem. aug: au: Kim, Sun Lee, Young Kim, Sun Hoon Lee, Young Hoon affil: Department of information and Industrial Engineering , Yonsei University , 50 Yonsei-Ro Seodaemun-Gu 120-749 Korea sug: subj: Ambulances Statistics and Numerical Data Computer Simulation Algorithms Reproducibility of Results Decision Making Statistics Linear Regression Time Factors ab: The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This paper studies an iterative optimization algorithm with parameter estimation to solve the emergency vehicle location problem. In the suggested algorithm, a linear model determines the locations of ambulances, while a hypercube simulation is used to estimate and provide parameters regarding ambulance locations. First, we suggest an iterative hypercube optimization algorithm in which interaction parameters and rules for the hypercube and optimization are identified. The interaction rules employed in this study enable our algorithm to always find the locations of ambulances satisfying the reliability requirement. We also propose an iterative simulation optimization algorithm in which the hypercube method is replaced by a simulation, to achieve computational efficiency. The computational experiments show that the iterative simulation optimization algorithm performs equivalently to the iterative hypercube optimization. The suggested algorithms are found to outperform existing algorithms suggested in the literature. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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