Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection

Abstract

Development of an efficient and effective home health care (HHC) service system is a quite recent and challenging task for the HHC firms. This paper aims to develop an HHC service system in the perspective of long-term economic sustainability as well as operational efficiency. A more flexible mixed-integer linear programming (MILP) model is formulated by incorporating the dynamic arrival and departure of patients along with the selection of new patients and nursing staff. An integrated model is proposed that jointly addresses: (i) patient selection; (ii) nurse hiring; (iii) nurse to patient assignment; and (iv) scheduling and routing decisions in a daily HHC planning problem. The proposed model extends the HHC problem from conventional scheduling and routing issues to demand and capacity management aspects. It enables an HHC firm to solve the daily scheduling and routing problem considering existing patients and nursing staff in combination with the simultaneous selection of new patients and nurses, and optimizing the existing routes by including new patients and nurses. The model considers planning issues related to compatibility, time restrictions, contract durations, idle time and workload balance. Two heuristic methods are proposed to solve the model by exploiting the variable neighborhood search (VNS) approach. Results obtained from the heuristic methods are compared with a CPLEX based solution. Numerical experiments performed on different data sets, show the efficiency and effectiveness of the solution methods to handle the considered problem.

Bicriteria Vehicle Routing Problem with Preferences and Timing Constraints in Home Health Care Services

“…TW Simu Pre f Q Prec Reg [45] × × [46] × × × [47] × × × [48] × × [49] × × × [50] × × [47] × × × [48] × × [49] × × × [50] × × [51] × × × [52] × [53] × × × [54] × × × [55] × × [56] × × [57] × Table 4 shows that time windows and qualification are considered in the majority of the reviewed papers. However, some characteristics such as simultaneous synchronization, precedence synchronization, and periodicity have attracted less interest in the literature.…”

“…Cont. [38] × [37] × [39] × × [1] × [40] × [41] × [42] × [43] × × [44] × [45] × [46] × × [47] × × [48] × × [49] × [50] × [51] × × [52] × × [53] × [54] × × [55] × × [56] × × [57] × From this literature review on vehicle routing problems related to the HHC context, It can be seen that most of proposed methods are metaheuristics and that most of papers present a mathematical method (mixed integer linear program) by mean of solvers. Furthermore, the majority of studies involving different objectives considered an aggregated function defined as a weighted sum of the considered criteria.…”

“…The last trends seem to focus either on uncertainties or dynamic data ([62] studied a pick-up and delivery version of HHC with travel time uncertainty; [63] worked on the caregiver routing problem solved in a dynamic context with uncertainties and random events by a multi-agent system; [53] proposed a dynamic method to handle sudden incidents in practice; and [54] considered the dynamic arrival and departure of patients and nursing staff to solve the daily scheduling and routing problem in a long-term perspective). However, none of those dealt with multi-objective functions.…”

“…Cont. [21] × × × [22] × × × [23] × × × [24] × × × × [25] × × × [26] × [27] × [28] × [29] × [30] × [31] × [32] × [33] × × [34] × × [35] × × [36] × × [37] × × × [38] × × [39] × × × [1] × × [40] × × [41] × × [42] × [43] × [44] × [45] × [46] × [47] × × × [48] × [49] × [50] × × × [51] × × × [52] × [53] × [54] × × × [55] × × [56] × [57] × As shown in the last table, the objective of minimizing traveling costs, waiting costs, or patient preferences is undoubtedly the most widespread in the literature. However, when multiple objective functions are handled, they are often considered within a single criterion as a weighted sum.…”

Scheduling Nurse Shifts Using Goal Programming based on Nurse Preferences: A Case Study in an Emergency Department

“…It should be noted that due to an increasing focus on home care services, many nurse scheduling programs have been conducted in this field. Nasir and Dang [18] led a study on nurse scheduling of home care services. They applied mathematical modeling focused simultaneously on four problems: the patient selection, nurse fare, nurse allocation to each patient, and decision-making scheduling of home care services.…”