The authors are grateful to the Foundation for Science and Technology (FCT, Portugal)
for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020
and UIDP/05757/2020), SusTEC (LA/P/0007/2021) and ALGORITMI Research Centre / LASI
(UIDB/00319/2020). Filipe Alves thanks the FCT for supporting its research with the Ph.D. grant
SFRH/BD/143745/2019.
The increase in life expectancy has led to a growing demand for Home Health Care (HHC)
services. However, some problems can arise in the management of these services, leading to high
computational complexity and time-consuming to obtain an exact and/or optimal solution. This
study intends to contribute to an automatic multi-criteria decision-support system that allows the
optimization of several objective functions simultaneously, which are often conflicting, such as costs
related to travel (distance and/or time) and available resources (health professionals and vehicles) to
visit the patients. In this work, the HHC scheduling and routing problem is formulated as a multi objective approach, aiming to minimize the travel distance, the travel time and the number of vehicles,
taking into account specific constraints, such as the needs of patients, allocation variables, the health
professionals and the transport availability. Thus, the multi-objective genetic algorithm, based on the
NSGA-II, is applied to a real-world problem of HHC visits from a Health Unit in Bragança (Portugal),
to identify and examine the different compromises between the objectives using a Pareto-based
approach to operational planning. Moreover, this work provides several efficient end-user solutions,
which were standardized and evaluated in terms of the proposed policy and compared with current
practice. The outcomes demonstrate the significance of a multi-criteria approach to HHC services.
