Prioritized single nurse routing and scheduling for home healthcare services

Cinar, Ahmet; Salman, Serdar; Bozkaya, Burçin

doi:10.1016/j.ejor.2019.07.009

Cited by 44 publications

(21 citation statements)

References 28 publications

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“…Recent studies continue to focus on the development of new solutions for the home healthcare logistics [37][38][39][40][41][42][43][44][45][46][47][48][49][50]. For example, Fathollahi-Fard et al [40] proposed a solution, based on the Lagrangian relaxation theory, for home healthcare routing with a travel balancing supposition.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

2022

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Today, research on healthcare logistics is an important challenge in developing and developed countries, especially when a pandemic such as COVID-19 occurs. The responses required during such a pandemic would benefit from an efficiently designed model for robust and sustainable healthcare logistics. In this study, we focus on home healthcare logistics and services for planning the routing and scheduling of caregivers to visit patients’ homes. Due to the need for social distancing during the COVID-19 pandemic, these services are highly applicable for reducing the growth of the epidemic. In addition to this challenge, home healthcare logistics and services must be redesigned to meet the standards of a triple bottom line approach based on sustainable development goals. A triple bottom line approach finds a balance between economic, environmental, and social criteria for making a sustainable decision. Although, recently, the concept of green home healthcare has been studied based on the total cost and green emissions of home healthcare logistics and services, as far as we know, no research has been conducted on the formulation of a triple bottom line approach for home healthcare logistics and services. To achieve social justice for caregivers, the goal of balancing working time is to find a balance between unemployment time and overtime. Another contribution of this research is to develop a scenario-based robust optimization approach to address the uncertainty of home healthcare logistics and services and to assist with making robust decisions for home healthcare planning. Since our multi-objective optimization model for sustainable and robust home healthcare logistics and services is more complex than other studies, the last novel contribution of this research is to establish an efficient heuristic algorithm based on the Lagrangian relaxation theory. An initial solution is found by defining three heuristic algorithms. Our heuristic algorithms use a symmetric pattern for allocating patients to pharmacies and planning the routing of caregivers. Then, a combination of the epsilon constraint method and the Lagrangian relaxation theory is proposed to generate high-quality Pareto-based solutions in a reasonable time period. Finally, an extensive analysis is done to show that our multi-objective optimization model and proposed heuristic algorithm are efficient and practical, as well as some sensitivities are studied to provide some managerial insights for achieving sustainable and robust home healthcare services in practice.

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Section: Literature Reviewmentioning

confidence: 99%

Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

2022

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“…This is also an important goal of “self-interested” platforms, as their revenues are derived from matched tasks. These matched tasks may have different priorities ( Cinar et al, 2019 ; M. Lin et al, 2016 ). Each caregiver has a predefined qualification that is a function of the caregiver, sex constraints, or language skills ( Braekers et al, 2016 , Cappanera and Scutellà, 2015 , Cappanera et al, 2018 , Eveborn et al, 2009 , Grenouilleau et al, 2019 , Lin et al, 2018 , Maya Duque et al, 2015 , Mosquera et al, 2019 , Nickel et al, 2012 , Rest and Hirsch, 2016 , Yalçındağ et al, 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Matching daily home health-care demands with supply in service-sharing platforms

Lin

Ying

2021

Transportation Research Part E: Logistics and Transportation Re

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Highlights Match daily home health-care demand with supply on service-sharing platforms. Develop an effective branch-and-price approach for the daily matching problem. Consider factors such as flexible service duration, break, and temporal dependency. Analyze four matching strategies in different stages for service-sharing platforms.

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“…Since metaheuristics use the continuous search space, an encoding representation is needed to generate the feasible solutions to cover the constraints of model [10,49]. This encoding representation also connects the optimization algorithms to the proposed optimization problem [50].…”

Section: Encoding Representationmentioning

confidence: 99%

“…From the perspective of home healthcare managers, there are two important challenges. The first one is the transportation cost associated with the logistics activities of caregivers [10]. Another concern is the availability of patients and caregivers [11].…”

Section: Introductionmentioning

confidence: 99%

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

Fathollahi-Fard

Ahmadi

Goodarzian

et al. 2020

Applied Soft Computing

126

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Home care services are an alternative answer to hospitalization, and play an important role in reducing the healthcare costs for governments and healthcare practitioners. To find a valid plan for these services, an optimization problem called the home healthcare routing and scheduling problem is motivated to perform the logistics of the home care services. Although most studies mainly focus on minimizing the total cost of logistics activities, no study, as far as we know, has treated the patients' satisfaction as an objective function under uncertainty. To make this problem more practical, this study proposes a bi-objective optimization methodology to model a multi-period and multi-depot home healthcare routing and scheduling problem in a fuzzy environment. With regards to a group of uncertain parameters such as the time of travel and services as well as patients' satisfaction, a fuzzy approach named as the Jimenez's method, is also utilized. To address the proposed home healthcare problem, new and well-established metaheuristics are obtained. Although the social engineering optimizer (SEO) has been applied to several optimization problems, it has not yet been applied in the healthcare routing and scheduling area. Another innovation is to develop a new modified multi-objective version of SEO by using an adaptive memory strategy, so-called AMSEO. Finally, a comprehensive discussion is provided by comparing the algorithms based on multi-objective metrics and sensitivity analyses. The practicality and efficiency of the AMSEO in this context lends weight to the development and application of the approach more broadly.

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Prioritized single nurse routing and scheduling for home healthcare services

Cited by 44 publications

References 28 publications

Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

Sustainable and Robust Home Healthcare Logistics: A Response to the COVID-19 Pandemic

Matching daily home health-care demands with supply in service-sharing platforms

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

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