Browsing by Author "Çayırlı, Tuğba"
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The 39th international conference of the EURO working group on operational research applied to health services: ORAHS 2013 special issue
Çayırlı, Tuğba; Gunal, M. M.; Gunes, E.; Ormeci, L. (Springer Science+Business Media, 2015-09)The healthcare sector is facing major challenges worldwide in terms of higher demands for efficiency, quality and equity. Operational Research (OR) techniques offer valuable tools for improving the design and delivery of ... -
Assessment of patient classification in appointment system design
Çayırlı, Tuğba; Veral, E.; Rosen, H. (Production and Operations Management Society, 2008-05)This paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and ... -
Outpatient appointment scheduling in presence of seasonal walk-ins
Çayırlı, Tuğba; Güneş, E. D. (Springer Nature, 2014-04)This study investigates appointment systems (AS), as combinations of access rules and appointment-scheduling rules, explicitly designed for dealing with walk-in seasonality. In terms of 'access rules', strategies are tested ... -
Predicting the performance of queues–A data analytic approach
Yang, K. K.; Çayırlı, Tuğba; Low, J. M.W. (Elsevier, 2016)Existing models of multi-server queues with system transience and non-standard assumptions are either too complex or restricted in their assumptions to be used broadly in practice. This paper proposes using data analytics, ... -
A universal appointment rule in the presence of no-shows and walk-ins
Çayırlı, Tuğba; Yang, K. K.; Quek, S. A. (Wiley, 2012-07)This study introduces a universal “Dome” appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factors—no-shows, walk-ins, number of appointments ... -
A universal appointment rule with patient classification for service times, no-shows and walk-ins
Çayırlı, Tuğba; Yang, K. K. (Informs, 2014)This study evaluates patient classification for scheduling and sequencing appointments for patients differentiated by their mean and standard deviation of service times, no-show, and walk-in probabilities. Alternative ...
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