Authors:
F. Alves
1
;
F. Alvelos
2
;
A. M. A. C. Rocha
2
;
Ana I. Pereira
1
and
Paulo Leitão
3
Affiliations:
1
Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal, Algoritmi R&D Centre, University of Minho, Braga and Portugal
;
2
Department of Production and Systems, Algoritmi Research Centre, University of Minho, Braga and Portugal
;
3
Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança and Portugal
Keyword(s):
Home Health Care, Operations Research, Periodic Vehicle Routing.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Operational Research
;
OR in Health
;
Pattern Recognition
;
Routing
;
Scheduling
;
Software Engineering
;
Symbolic Systems
Abstract:
In logistics of home health care services in the Health Units, the managers and nurses need to carry out the schedule and the vehicles routes for the provision of care at the patients’ homes. Currently, in Portugal, these services are increasingly used but the problem is still, usually, solved manually and without computational resources. The increased demand for home health care due to the boost of the elderly people number entails a high associated cost which, sometimes, does not guarantee the quality of the service. In this sense, the periodic vehicle routing problem is a generalization of the classical vehicle routing problem in which routes are determined for a time horizon of several days. In this work, it is provided a periodic vehicle routing problem applied in the Health Unit in Bragança. An integer linear programming formulation for the real database, allowed to solve the problem in an efficient and optimized way using the CPLEX
R software.