Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

Mascolo, Maria Di; Martinez, Cléa; Espinouse, Marie‐Laure

doi:10.1016/j.cie.2021.107255

Cited by 62 publications

(13 citation statements)

References 173 publications

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“…Nasir and Kuo [11] only consider the minimum total travel cost of staff but have synchronization constraints between nurses and vehicles as they consider the travel costs of the two separately. Cissé et al [12] and Mascolo et al [13] give the most recent extended review of literature in HHC routing and scheduling problems with variety of constraints to date.…”

Section: Methodsmentioning

confidence: 99%

Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System

Saksuriya

Likasiri

2022

Applied Sciences

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This work involves a heuristic for solving vehicle routing problems with time windows (VRPTW) with general compatibility-matching between customer/patient and server/caretaker constraints to capture the nature of systems such as caretakers’ home visiting systems or home healthcare (HHC) systems. Since any variation of VRPTW is more complicated than regular VRP, a specific, custom-made heuristic is needed to solve the problem. The heuristic proposed in this work is an efficient hybrid of a novice Local Search (LS), Ruin and Recreate procedure (R&R) and Particle Swarm Optimization (PSO). The proposed LS acts as the initial solution finder as well as the engine for finding a feasible/local optimum. While PSO helps in moving from current best solution to the next best solution, the R&R part allows the solution to be over-optimized and LS moves the solution back on the feasible side. To test our heuristic, we solved 56 benchmark instances of 25, 50, and 100 customers and found that our heuristics can find 52, 21, and 18 optimal cases, respectively. To further investigate the proficiency of our heuristic, we modified the benchmark instances to include compatibility constraints. The results show that our heuristic can reach the optimal solutions in 5 out of 56 instances.

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Section: Methodsmentioning

confidence: 99%

Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System

Saksuriya

Likasiri

2022

Applied Sciences

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“…Since home healthcare services have recently become important as a solution for hospitalization problems, researchers have proposed optimization techniques to help practitioners in this industry [13][14][15][16]. Although there are some review papers on this research area [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33], in this review, we provide the most important and recent studies which have made a significant contribution to home healthcare services and logistics.…”

Section: Literature Reviewmentioning

confidence: 99%

“…These objectives and constraints make our sustainable and robust home healthcare logistics network more complex than other studies and this fact highlights the need for an intelligent solution algorithm for this problem. Home healthcare logistics and services are an extension to the problem of route optimization [11][12][13][14]. Classically, home healthcare logistics have been shown to be an NP-hard problem in the strong sense [15,16].…”

Section: Introductionmentioning

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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“…In this section, we focus primarily on the literature in tactical level which our problem lies in, i.e., papers that apply stochastic optimization to address HSCP problems similar to ours. For comprehensive recent surveys of operations research methods applied to decisions in home health care, we refer readers to Gutiérrez & Vidal (2013), Fikar & Hirsch (2017), Grieco et al (2021) and Di Mascolo et al (2021). We also refer to Michael (2018) for a comprehensive survey of scheduling theory, applications and methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Home Care Staffing and Capacity Planning: Stochastic Optimization Approaches

Wang¹,

Shehadeh²,

Xie³

et al. 2022

Preprint

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We propose stochastic optimization methodologies for a staffing and capacity planning problem arising from home care practice. Specifically, we consider the perspective of a home care agency that must decide the number of caregivers to hire (staffing) and the allocation of hired caregivers to different types of services (capacity planning) in each day within a specified planning horizon. The objective is to minimize the total cost associated with staffing (i.e., employment), capacity allocation, over-staffing, and under-staffing. We propose two-stage stochastic programming (SP) and distributionally robust optimization (DRO) approaches to model and solve this problem considering two types of decision-makers, namely an everything in advance decision-maker (EA) and a flexible adjustment decision-maker (FA). In the EA models, we determine the staffing and capacity allocation decisions in the first stage before observing the demand. In the FA models, we decide the staffing decisions in the first stage. Then, we determine the capacity allocation decisions based on demand realizations in the second stage.We derive equivalent mixed-integer linear programming (MILP) reformulations of the proposed nonlinear DRO model for the EA decision-maker that can be implemented and efficiently solved using off-the-shelf optimization software. We propose a computationally efficient column-andconstraint generation algorithm with valid inequalities to solve the proposed DRO model for the FA decision-maker. Finally, we conduct extensive numerical experiments comparing the operational and computational performance of the proposed approaches and discuss insights and implications for home care staffing and capacity planning.

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Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

Cited by 62 publications

References 173 publications

Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System

Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System

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

Integrated Home Care Staffing and Capacity Planning: Stochastic Optimization Approaches

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