Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104508
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Title: Appointment scheduling optimization for specialist outpatient services
Authors: Lee, CKM 
Ng, KKH 
Cheng, MC 
Issue Date: 2018
Source: Proceedings of the 2nd European Conference on Industrial Engineering and Operations Management (IEOM), Paris, France, July 26-27, 2018, p. 876-883
Abstract: Aging population and expecting a higher living standard in the developed countries cause demanding and high quality service in healthcare industry respectively. However, one of the customer requirement is to reduce the waiting time to see the doctor in the high demand of public medical.As a result, service appointment scheduling is the important issue. The poor medical service scheduling may lead to the complaints from patients on waiting time. Researchers tried to minimize the hospital explicit and implicit cost and maximize patient’s satisfaction by adopting the appointment scheduling rules. The trade-off is considered in appointment scheduling problem. In general, solving appointment scheduling problem includes simulation and analytical method. The proposed approach allows hospital to take as a reference to further improve the appointment scheduling system. In this research, appointment scheduling optimization model with LINGO software using the exact algorithm is applied into the appointment scheduling problem for the outpatient clinic. The performance of the appointment scheduling optimization model is examined in difference case scenario and performance improvement is realized.
Keywords: Appointment scheduling optimization model
Appointment scheduling problem
LINGO
Publisher: IEOM Society
ISBN: 978-1-5323-5945-3
Rights: © IEOM Society International
The following publication Lee, C. K. M., Ng, K. K. H., & Cheng, M. C. (2018, January). Appointment scheduling optimization for specialist outpatient services. In Proceedings of the 2nd European conference on industrial engineering and operations management (IEOM) (pp. 876-883) is available at https://ieomsociety.org/paris2018/proceedings/.
Appears in Collections:Conference Paper

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