TY - JOUR
T1 - Development of a Doctor Scheduling System: A Constraint Satisfaction and Penalty Minimisation Scheduling Model
AU - Chawasemerwa, T
AU - Taifa, I W
AU - Hartmann, D
PY - 2018
Y1 - 2018
N2 - Doctor scheduling is a complex, costly and time-consuming exercise. This study develops a constraint satisfaction and penalty minimisation scheduling model for meeting 'hard constraints' and minimises the cost of violating 'soft constraints', i.e. the user inputs, the total number of doctors to be scheduled, the maximum penalty to be met, and the minimum number of doctors to be assigned per shift. The algorithm creates a schedule which checks against all the constraints. The total schedule penalty associated with the constraint violations should be less than or equal to the user input penalty. If this condition is met, the schedule gets produced as the final and near-optimal solution. The model is managed to create a near optimal schedule with the minimal rule violations. However, it is challenging to provide a schedule with no rule violations. Such a situation is shown by the amount of computational time required to create a zero-penalty schedule, hours or even days needed to create a zero-penalty schedule. The system creates a schedule for a short period (weekly schedule) to promote flexibility; however, such a system does not promote fairness. Fairness is achieved through a cyclic schedule with rotations equal to the total number of doctors being scheduled. The system is managed to create a streamlined and flexible working environment and helped to improve the quality of healthcare. An optimization protocol can be incorporated into the system to reduce the search space and get the best optimal schedule since it is possible to get many schedules under the same user-defined parameters.
AB - Doctor scheduling is a complex, costly and time-consuming exercise. This study develops a constraint satisfaction and penalty minimisation scheduling model for meeting 'hard constraints' and minimises the cost of violating 'soft constraints', i.e. the user inputs, the total number of doctors to be scheduled, the maximum penalty to be met, and the minimum number of doctors to be assigned per shift. The algorithm creates a schedule which checks against all the constraints. The total schedule penalty associated with the constraint violations should be less than or equal to the user input penalty. If this condition is met, the schedule gets produced as the final and near-optimal solution. The model is managed to create a near optimal schedule with the minimal rule violations. However, it is challenging to provide a schedule with no rule violations. Such a situation is shown by the amount of computational time required to create a zero-penalty schedule, hours or even days needed to create a zero-penalty schedule. The system creates a schedule for a short period (weekly schedule) to promote flexibility; however, such a system does not promote fairness. Fairness is achieved through a cyclic schedule with rotations equal to the total number of doctors being scheduled. The system is managed to create a streamlined and flexible working environment and helped to improve the quality of healthcare. An optimization protocol can be incorporated into the system to reduce the search space and get the best optimal schedule since it is possible to get many schedules under the same user-defined parameters.
KW - Constraint satisfaction model
KW - Healthcare centres
KW - Model development
KW - Optimisation protocol
KW - Particle swarm optimisation
KW - Scheduling system
KW - Soft constraints
UR - http://www.riejournal.com/article_80629.html
UR - http://www.mendeley.com/research/development-doctor-scheduling-system-constraint-satisfaction-penalty-minimisation-scheduling-model
U2 - 10.22105/riej.2018.160257.1068
DO - 10.22105/riej.2018.160257.1068
M3 - Article
VL - 7
SP - 396
EP - 422
JO - International Journal of Research in Industrial Engineering
JF - International Journal of Research in Industrial Engineering
IS - 4
ER -