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HEC-Ecole de gestion de l'Université de Liège
HEC-Ecole de gestion de l'Université de Liège
MASTER THESIS
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A Heuristic Approach to the Home Healthcare Districting Problem in the Province of Liège

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Dogan, Furkan ULiège
Promotor(s) : François, Véronique ULiège
Date of defense : 4-Sep-2023/8-Sep-2023 • Permalink : http://hdl.handle.net/2268.2/18799
Details
Title : A Heuristic Approach to the Home Healthcare Districting Problem in the Province of Liège
Translated title : [fr] Une approche heuristique de la problématique de répartition territoriale des soins à domicile en Province de Liège
Author : Dogan, Furkan ULiège
Date of defense  : 4-Sep-2023/8-Sep-2023
Advisor(s) : François, Véronique ULiège
Committee's member(s) : Maharani, Anisha ULiège
Language : English
Number of pages : 66
Keywords : [fr] home health care, tactical level, nurses, patients, districting, home healthcare districting, simulated annealing, heuristic, workload, optimisation
Discipline(s) : Business & economic sciences > Production, distribution & supply chain management
Business & economic sciences > Special economic topics (health, labor, transportation...)
Target public : Researchers
Professionals of domain
Student
General public
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master en ingénieur de gestion, à finalité spécialisée en Supply Chain Management and Business Analytics
Faculty: Master thesis of the HEC-Ecole de gestion de l'Université de Liège

Abstract

[fr] In recent years, home healthcare (HHC) has gained increasing importance, particularly in developed countries, due to an aging population and changing family structures. The demand for efficient HHC districting has become crucial to control costs and optimize resources in healthcare agencies. This master thesis addresses the needs and improvements in HHC districting, focusing on the specific case of the Province of Liège.
The document commences by providing an insightful overview of the challenges associated with home healthcare and districting, emphasizing the growing significance of HHC in the healthcare landscape. It then proceeds to conduct an in-depth review of existing literature on the subject, gaining valuable insights from previous studies.
The thesis proposes an innovative extension of the solution method developed by Ozturk et al. (2022) to tackle the unique challenges faced in HHC districting within the Province of Liège. The extension incorporates travel load into the objective function through two distinct scenarios and integrates contiguity constraints that take into consideration the geographical layout and specific requirements of the region. In order to enhance the solution method's effectiveness, a simulated annealing approach is integrated into the heuristic, providing a powerful technical optimisation.
The proposed heuristic is subject to rigorous computational experiments to evaluate its performance with a focus on workload balance, computation time, and solution quality. The results demonstrate its promising efficacy, showcasing an efficient workload distribution within a remarkably short computation time. By achieving a more balanced distribution of workloads, the proposed method enables healthcare providers to optimise their resources and deliver quality care directly to patients' doorsteps.
While the thesis offers substantive contributions, it also identifies prospective avenues for future research. Specifically, further exploration is needed to calculate the shortest path between basic units, refining the formation of basic units based on similar care loads and investigating the characteristics of HHC patient profiles in Belgium.
In conclusion, this master thesis provides a comprehensive and pragmatic study on home healthcare districting. It not only identifies the challenges faced in HHC but also offers novel insights and a tailored approach specifically designed for the Province of Liège. By revolutionising the way healthcare providers manage their resources, this research contributes significantly to improve home healthcare services and ensure better patient outcomes.


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Access Master_thesis_final.pdf
Description:
Size: 1.21 MB
Format: Adobe PDF

Annexe(s)

File
Access data_final.xlsx
Description: data to use in julia
Size: 78.35 kB
Format: Microsoft Excel XML
File
Access first_scenario.jl
Description: first scenario julia code
Size: 24.27 kB
Format: Unknown
File
Access first_scenario_ozturk.jl
Description: first scenario using Ozturk julia code
Size: 15.48 kB
Format: Unknown
File
Access second_scenario.jl
Description: second scenario julia code
Size: 25.4 kB
Format: Unknown
File
Access second_scenario_Ozturk.jl
Description: second scenario using Ozturk julia code
Size: 13.88 kB
Format: Unknown
File
Access modified.xlsx
Description: dataset construction file
Size: 90.14 kB
Format: Microsoft Excel XML

Author

  • Dogan, Furkan ULiège Université de Liège > Master ingé. gest., à fin.

Promotor(s)

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  • Total number of views 170
  • Total number of downloads 141










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