Patient Scheduling under Uncertainty and Hospital Resource Allocation with Patient Waiting Time, Personnel Overtime and Idleness Minimization Approach and with Application of Queuing Theory and Analytical Tools

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Mirmajidi Nezami, Ali | 2021

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 55203 (01)
University: Sharif University of Technolog
Department: Industrial Engineering
Advisor(s): Shadrokh, Shahram
Abstract:
Scheduling problem specially surgery room scheduling is noteworthy and well known in optimization and machine learning literature which improve resource usage means cost reduction and patient experience means satisfaction increase.Surgery Rooms are one of the most costly section of the hospital. In addition to this, Surgeon are expensive resource and all the hospitals have limited capacity. By scheduling we can improve patient’s experience and resource management. That’s why scheduling Surgery Room is important and noteworthy.In this research we consider surgery duration and patient length of stay(LOS) probabilistic. Our approach for handling this is stochastic programming in which our surgery duration variable follows normal distribution however LOS best fitted distribution is Poisson distribution.Basically surgery duration has no well known distribution where we used unsupervised machine learning method called clustering method in which we have normal distribution in each cluster.Our objective function consists of three part:•Minimize bed needed capacity variance in each block;•Minimize patient queue;•Maximize number of surgery.
Keywords:
Stochastic Optimization ; Machine Learning ; Clustering ; Operating Room Scheduling ; Patient Waiting Time ; Queuing Theory

No TOC