Metaheuristics for solving a multimodal home-healthcare scheduling problem

Abstract We present a general framework for solving a real-world multimodal home-healthcare scheduling (MHS) problem from a major Austrian home-healthcare provider. The goal of MHS is to assign home-care staff to customers and determine efficient multimodal tours while considering staff and customer satisfaction. Our approach is designed to be as problem-independent as possible, such that the resulting methods can be easily adapted to MHS setups of other home-healthcare providers. We chose a two-stage approach: in the first stage, we generate initial solutions either via constraint programming techniques or by a random procedure. During the second stage, the initial solutions are (iteratively) improved by applying one of four metaheuristics: variable neighborhood search, a memetic algorithm, scatter search and a simulated annealing hyper-heuristic. An extensive computational comparison shows that the approach is capable of solving real-world instances in reasonable time and produces valid solutions within only a few seconds

Home health care logistics planning: a review and framework

Home Health Care (HHC) is a growing industry in the medical services business, mainly in Europe and North America. These care services are provided at patients’ home by a multidisciplinary team using a distribution network. In this paper, an overview of the HHC services in Portugal and Brazil is presented. Additionally, a review is also presented to identify the main logistics problems associated with HHC services such as districting, routing and inventory management and the lack of integrated approaches to address them, as well as the best practices of management in the area. A framework is proposed to represent the main elements and characteristics of HHC services and their relationships. The framework suggests the use of a Decision Support System (DSS) based on optimization models and simulation approaches to overcome some of the main challenges associated to integrated approaches to address main problems, filling the gaps in the current literature. With the development of this DSS it will be possible to assist in the logistic planning of HHC teams, especially in countries like Brazil and Portugal.This work has been supported by CNPq (National Counsel of Technological and Scientific Development, Brazil) and COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Scheduling Sustainable Homecare with Urban Transport and Different Skilled Nurses Using an Approximate Algorithm

The essential characteristics that distinguish homecare services from other routing and scheduling problems are relatively few patients being spread out over a large urban area, long transport times and several different services being provided. The approach that the authors present herein was developed to solve planning homecare services according to the criterion of increasing social sustainability and incorporating environmentally sustainable transport systems. The objective of this paper is to present a tool to plan the daily work carried out by a homecare service with assigned patients with specific care requirements. It relies on the resources of nurses with different qualifications by assuming costs that depend on both offering the service and the different chosen transport modes. The algorithm manages several priority rules by ensuring that homecare provider goals and standards are met. The developed algorithm was tested according to the weekly homecare schedule of a group of nurses in a medium-sized European city and was successfully used during validation to improve homecare planning decisions. The results, therefore, are not generalisable but its modular structure ensures its applicability to different cases. The algorithm provides a patient-centred visiting plan and improves transport allocation by offering nurses a better route assignment by considering the required variables and each nurse's daily workload.This research was founded Young Researcher Training granted by the Mediterranean Institute for Advanced Studies (MEDIFAS) according to the contract reached between the Slovenian Research Agency (ARRS) and MEDIFAS

Dynamically accepting and scheduling patients for home healthcare

The importance of home healthcare is growing rapidly since populations of developed and even developing countries are getting older and the number of hospitals, retirement homes, and medical staff do not increase at the same rate. We consider the Home Healthcare Nurse Scheduling Problem where patients arrive dynamically over time and acceptance and appointment time decisions have to be made as soon as patients arrive. The objective is to maximise the average number of daily visits for a single nurse. For the sake of service continuity, patients have to be visited at the same day and time each week during their episode of care. We propose a new heuristic based on generating several scenarios which include randomly generated and actual requests in the schedule, scheduling new customers with a simple but fast heuristic, and analysing results to decide whether to accept the new patient and at which appointment day/time. We compare our approach with two greedy heuristics from the literature, and empirically demonstrate that it achieves significantly better results compared to these other two methods

The sustainable home health care process based on multi-criteria decision-dupport

The increase in life expectancy has led to a growing demand for Home Health Care (HHC) services. However, some problems can arise in the management of these services, leading to high computational complexity and time-consuming to obtain an exact and/or optimal solution. This study intends to contribute to an automatic multi-criteria decision-support system that allows the optimization of several objective functions simultaneously, which are often conflicting, such as costs related to travel (distance and/or time) and available resources (health professionals and vehicles) to visit the patients. In this work, the HHC scheduling and routing problem is formulated as a multi objective approach, aiming to minimize the travel distance, the travel time and the number of vehicles, taking into account specific constraints, such as the needs of patients, allocation variables, the health professionals and the transport availability. Thus, the multi-objective genetic algorithm, based on the NSGA-II, is applied to a real-world problem of HHC visits from a Health Unit in Bragança (Portugal), to identify and examine the different compromises between the objectives using a Pareto-based approach to operational planning. Moreover, this work provides several efficient end-user solutions, which were standardized and evaluated in terms of the proposed policy and compared with current practice. The outcomes demonstrate the significance of a multi-criteria approach to HHC services.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020), SusTEC (LA/P/0007/2021) and ALGORITMI Research Centre / LASI (UIDB/00319/2020). Filipe Alves thanks the FCT for supporting its research with the Ph.D. grant SFRH/BD/143745/2019.info:eu-repo/semantics/publishedVersio

Planning the delivery of home-based long-term care: A mathematical programming-based tool to support routes' planning

The adequate planning of home-based long-term care (HBLTC) is essential in the current European setting where long-term care (LTC) demand is increasing rapidly, and where home-based care represents a potential cost-saving alternative from traditional inpatient care. Particularly, this planning should involve proper route planning to ensure visits of health professionals to patients’ homes. Nevertheless, literature in the specific area of HBLTC planning is still scarce. Accordingly, this paper proposes a tool based on a mathematical programming model – the LTCroutes – for supporting the daily planning of routes to visit LTC patients’ homes in National Health Service-based countries. The model allows exploring the impact of considering different objectives relevant in this sector, including the minimization of costs and the maximization of service level. Patients’ preferences, traffic conditions and budget constraints are also considered in the proposed model. To illustrate the applicability of the model, a case study based on the National Network of LTC in Portugal (RNCCI) is analysed.O planeamento adequado de cuidados continuados ao domicílio é essencial na conjuntura atual Europeia em que a procura de cuidados continuados está a aumentar rapidamente, e em que os cuidados ao domicílio representam uma alternativa com potencial de poupança de custos relativamente ao tradicional internamento hospitalar. Particularmente, é necessário haver um planeamento adequado das rotas dos profissionais de saúde às casas dos pacientes. No entanto, a literatura na área específica de planeamento de cuidados continuados ao domicílio ainda é escassa. Nesse sentido, este artigo propõe uma ferramenta baseada num modelo de programação matemática - o LTCroutes - para apoiar o planeamento diário das rotas para visitar as casas dos pacientes com necessidade de cuidados continuados em países com Serviço Nacional de Saúde. O modelo desenvolvido permite explorar o impacto de considerar diferentes objetivos relevantes neste setor, incluindo a minimização de custos e a maximização do nível de serviço. As preferências dos pacientes, condições de trânsito e restrições de orçamento também são consideradas no modelo proposto. Para ilustrar a aplicabilidade do modelo, é analisado um caso de estudo baseado na Rede Nacional de Cuidados Continuados Integrados (RNCCI) em Portugal