Minimizing Total Clinical Deterioration in Operating Theatres

Mobina Mashkani, Hanyu Gu, Dhananjay Thiruvady, Andreas T. Ernst

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


Efficient operating theatre (OT) planning and scheduling contributes substantially to better utilization of a hospitalgh2019;s expensive resources and superior management of its complex operations. This study investigates the OT planning and scheduling problem at both tactical and operational decision levels to meet the hospital administration's expectations and patients' satisfaction simultaneously. The main goal is to concurrently allocate surgical specialties to operating rooms by developing a master surgery schedule (MSS), and solve the surgical case assignment problem (SCAP), which assigns a particular surgery day and time block to each elective patient. To minimize the total patients' clinical condition deterioration, we propose two dynamic programming based heuristic algorithms, a mixed integer programming model (MIP), and an iterated local search (ILS) approach. We perform extensive computational experiments with 1500 instances. The results demonstrate the efficacy of our heuristic algorithms as well as the proposed ILS, which generates high quality solutions across all problem instances with an average optimality gap of 1.51%.

Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781728125473, 9781728125466, 9781728125480
Publication statusPublished - 1 Dec 2020
EventIEEE Symposium Series on Computational Intelligence 2020 - Virtual, Canberra, Australia
Duration: 1 Dec 20204 Dec 2020


ConferenceIEEE Symposium Series on Computational Intelligence 2020
Abbreviated titleSSCI 2020
CityVirtual, Canberra
Internet address

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