scholarly journals A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment

2020 ◽  
Vol 93 ◽  
pp. 106385 ◽  
Author(s):  
Amir Mohammad Fathollahi-Fard ◽  
Abbas Ahmadi ◽  
Fariba Goodarzian ◽  
Naoufel Cheikhrouhou
Author(s):  
Mehmet Erdem ◽  
Serol Bulkan

In the home healthcare routing and scheduling problem (HHCRSP), nurses are allocated to a variety of services demanded by clients during a planning horizon. The properties of this problem resemble vehicle routing and nurse scheduling. To propose an efficient solution, the authors consider various issues such as multi-depot, travelling time, time windows, synchronisation, the qualification levels, and other features of nurses and clients. In addition, the continuity of care and work overload should not be ignored in this perspective. First, the authors developed a model in which the continuity of care is redefined by considering connected (synchronous) jobs and the work overload is formulated considering nurse-to-patient staffing ratio. Second, a two-stage solution approach based on a cluster-assign algorithm and variable neighbourhood search (VNS) and variable neighbourhood descent (VND) algorithms are tested on a series of large-scale instances. Computational results present the relations and trade-offs among the aforementioned issues.


2021 ◽  
pp. 373-382
Author(s):  
Fatemeh Taghipour ◽  
Reza Tavakkoli-Moghaddam ◽  
Maryam Eghbali-Zarch

2021 ◽  
Vol 10 (3) ◽  
pp. 217-230
Author(s):  
Jalel Euchi ◽  
Salah Zidi ◽  
Lamri Laouamer

Home health care faces new challenges day by day and it has become increasingly legitimate in the face of an aging population. Home healthcare centers are exposed to cumulative demands and academics are paying attention to the routing and scheduling matter, which is offered in literature as a Technician Routing and Scheduling Problem (TRSP) where the aim is to minimize the total cost subject to the time windows constraints to serve the patients respecting their priorities. In this paper, we develop a new distributed algorithm to resolve the home health care routing and scheduling problem (HHRSP). The principal idea of this algorithm is to apply artificial intelligence techniques in a distributed optimization method. The integration of automatic learning and search methods are applied to optimize the assignment of appointments to home caregivers. It allows us to gain time, effort, especially cost, and while complying with the problem constraints. The comparison results prove the efficacy of the recommended approach, which can offer decision support for medical executives of home health care.


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