TY - JOUR
T1 - Home visit scheduling for family interventions
T2 - a child protection case study
AU - de Aguiar, Ana Raquel Pena
AU - Grassi, Inês Clode de Freitas
AU - Gomes, Maria Isabel
AU - Ramos, Tânia Rodrigues Pereira
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00297%2F2020/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00297%2F2020/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00097%2F2020/PT#
info:eu-repo/grantAgreement/FCT/OE/SFRH%2FBD%2F148773%2F2019/PT#
Publisher Copyright:
© 2023 International Federation of Operational Research Societies.
PY - 2023/12/17
Y1 - 2023/12/17
N2 - Family dynamics affect the development of children and youth, which can even endanger young people and lead to the loss of parental rights and subsequent institutionalization. Recent emphasis has been placed on working with families when a potentially risky situation is identified, aiming at developing skills within family members and avoiding institutionalization. Some organizations help to develop the social skills necessary for families to change negative dynamics. The organizations are not for profit and often lack the knowledge to plan their activities efficiently, particularly in allocating human resources to design, implement, and schedule home visit interventions. This work is motivated by one such organization that works with families needing support by regularly making home visits to monitor interventions. Currently, visits are scheduled manually with the technicians trying to coordinate schedules with each other and with the families. The increasing number of families referenced to the organization has made it difficult to keep track of the time intervals between visits, especially since visits are frequently cancelled (e.g., changing availability, attending court hearings). This work proposes an optimization model to help technicians plan home visits. It accounts for the time availability of technicians and families while ensuring a service level based on the time between visits. In addition, the new Mixed Integer Programing model, which is based on the assignment problem, also takes into account technicians’ work–life balance, worktime exemption, and technicians’ visiting time preferences. The results show the model schedules more than 260% of home visits while increasing the capacity used by 25 percentage points, demonstrating its usefulness.
AB - Family dynamics affect the development of children and youth, which can even endanger young people and lead to the loss of parental rights and subsequent institutionalization. Recent emphasis has been placed on working with families when a potentially risky situation is identified, aiming at developing skills within family members and avoiding institutionalization. Some organizations help to develop the social skills necessary for families to change negative dynamics. The organizations are not for profit and often lack the knowledge to plan their activities efficiently, particularly in allocating human resources to design, implement, and schedule home visit interventions. This work is motivated by one such organization that works with families needing support by regularly making home visits to monitor interventions. Currently, visits are scheduled manually with the technicians trying to coordinate schedules with each other and with the families. The increasing number of families referenced to the organization has made it difficult to keep track of the time intervals between visits, especially since visits are frequently cancelled (e.g., changing availability, attending court hearings). This work proposes an optimization model to help technicians plan home visits. It accounts for the time availability of technicians and families while ensuring a service level based on the time between visits. In addition, the new Mixed Integer Programing model, which is based on the assignment problem, also takes into account technicians’ work–life balance, worktime exemption, and technicians’ visiting time preferences. The results show the model schedules more than 260% of home visits while increasing the capacity used by 25 percentage points, demonstrating its usefulness.
KW - assignment and scheduling problem
KW - home social intervention
KW - lexicographic optimization
KW - technician preferences
KW - workload balance
UR - http://www.scopus.com/inward/record.url?scp=85179976348&partnerID=8YFLogxK
U2 - 10.1111/itor.13416
DO - 10.1111/itor.13416
M3 - Article
AN - SCOPUS:85179976348
SN - 0969-6016
JO - International Transactions In Operational Research
JF - International Transactions In Operational Research
ER -