2684. A matheuristic approach for integrated healthcare timetabling problems
Invited abstract in session MC-10: Integrated Healthcare Timetabling Competition II, stream Automated Timetabling.
Monday, 12:30-14:00Room: Clarendon SR 1.06
Authors (first author is the speaker)
| 1. | Rosita Guido
|
| Department of Mechanical, Energy and Management Engineering, University of Calabria | |
| 2. | Antonio Candelieri
|
| University of Milano Bicocca | |
| 3. | Domenico Conforti
|
| DIMEG, Università della Calabria |
Abstract
The integrated healthcare timetabling problem (IHTP) is a complex combinatorial optimization task emerging from the unification of three critical planning problems in the healthcare sector: patient admission scheduling within a time window, surgical case scheduling, and nurse-to-room assignment. Complexity of IHTP relies on the interdependencies between these three problems, requiring innovative approaches to achieve feasible and high-quality solutions.
In this work, we adapt the matheuristic FiNeMath, which hybridizes mathematical programming and heuristic techniques, to address the IHTP effectively. A warm-start procedure provides a good initial feasible solution, then the approach systematically explores the vast solution space using a combination of exact methods and heuristic strategies. Experimental results on the thirty benchmark instances show that FiNeMath outperforms standalone methods in terms of solution quality, computational efficiency, and scalability. The approach represents a practical and flexible tool for healthcare managers, enabling optimal resource allocation and optimal scheduling while balancing operational constraints and stakeholder preferences. This work highlights the potential of matheuristic approaches in tackling large-scale, integrated optimization problems, especially in the healthcare sector.
Keywords
- Combinatorial Optimization
- Mathematical Programming
- Timetabling
Status: accepted
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