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An Agent-Based Simulation Approach To Model Hospital Logistics
Norwegian University of Science and Technology.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
Norwegian University of Science and Technology.
Norwegian University of Science and Technology.
2019 (English)In: International Journal of Simulation Modelling, ISSN 1726-4529, E-ISSN 1996-8566, Vol. 18, no 4, p. 654-665Article in journal (Refereed) Published
Abstract [en]

The increasing rate of hospital admissions has resulted in a commensurate increase in the number of treatments and surgeries performed, as well as resource and material usage, and requires planners to improve hospitals' internal logistics. Logistics modelling of internal goods and corresponding material handling systems and simulating future scenarios can provide planners with necessary decision support. Introducing an agent-based simulation model using historical data generated by an automated guided vehicle (AGV) in a case hospital facilitates analysing the goods delivery system's current status and potential countermeasures to improve internal logistics. In comparison with other industries, such as manufacturing, AGVs utilised in hospitals have to interact with persons, patients and elevators, transport several different types of goods and cover a sizeable multi-floor area. By including these factors, the simulation model represents an appropriate method to test different scenarios and improve delivery performance and AGV utilisation. The study highlights the constraints related to operating AGVs in dynamic environments, such as those encountered in hospitals.

Place, publisher, year, edition, pages
2019. Vol. 18, no 4, p. 654-665
Keywords [en]
Logistics; Hospital Logistics; Automated Guided Vehicle; Agent-Based Simulation; Performance Analysis
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-264585DOI: 10.2507/IJSIMM18(4)497ISI: 000500961000009Scopus ID: 2-s2.0-85077603297OAI: oai:DiVA.org:kth-264585DiVA, id: diva2:1374443
Note

QC 20191204

Available from: 2019-12-01 Created: 2019-12-01 Last updated: 2020-02-04Bibliographically approved

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