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ETD

Digital archive of theses discussed at the University of Pisa

 

Thesis etd-04062022-215614


Thesis type
Tesi di laurea magistrale
Author
RECORDARE, ALESSANDRA
URN
etd-04062022-215614
Thesis title
Pattern-based modeling with dynamic sessions and uncertainty management for Master Surgical Scheduling
Department
INFORMATICA
Course of study
DATA SCIENCE AND BUSINESS INFORMATICS
Supervisors
relatore Scutellà, Maria Grazia
Keywords
  • MSS problem
  • OR scheduling
  • robust modeling
Graduation session start date
22/04/2022
Availability
Withheld
Release date
22/04/2025
Summary
This thesis work is based on the creation of optimization models for the Master Surgical Scheduling (MSS) problem, i.e., given a scheduling horizon, a list of patients, a number of available beds, and a grid in which, for each day of the time horizon, the total number of hours available for each operating room, we must determine a schedule in which, for each day and for each operating room, a family of surgeries and the number of surgeries to be performed are assigned such that the number of patients does not exceed the number of available beds and that there is an appropriate balance between long and short scheduled surgeries.
The work is concerned with creating a deterministic model with dynamic session lengths, delegating to the model the division of days into blocks of time. It uses a pattern-based approach divided into two phases: the first phase deals with generating the patterns using three different objective functions, while the second phase deals with associating a pattern for each day of the planning horizon and for each operating room using two different objective functions. For the model experimentation we used the Branch&Bound technique. The results obtained show that the new model, being more flexible, returns better results than the model with static sessions defined a priori.
In the second phase of the thesis work, we formulated a robust model of the previously proposed model to handle the uncertainty due to the duration of the surgical operations.
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