Home health care routing and scheduling problem: A preventive approach

Vélez Rusinque, Diana Lorena; Rincón Mendieta, Manuel Esteban; Bautista Franco, Ana María; Villanueva Gómez, Rebeca

Home health care routing and scheduling problem: A preventive approach

dc.contributor.advisor	Montoya Casas, Carlos Eduardo
dc.contributor.advisor	Barrera Ferro, Oscar David
dc.contributor.author	Vélez Rusinque, Diana Lorena
dc.contributor.author	Rincón Mendieta, Manuel Esteban
dc.contributor.author	Bautista Franco, Ana María
dc.contributor.author	Villanueva Gómez, Rebeca
dc.contributor.evaluator	Jiménez Gordillo, Jose Fernando
dc.contributor.evaluator	Roldán Nariño, Raúl Fabián
dc.coverage.spatial	Colombia	spa
dc.date.accessioned	2022-08-24T13:36:23Z
dc.date.available	2022-08-24T13:36:23Z
dc.date.created	2022-07-05
dc.description.abstract	Due to several challenges in hospital service caused by the increasing demand for hospitalization, Home Health Care Service (HHCS) has become the best alternative for hospitals to provide a delivery service system that allows patients to be cared at their place of residence. The HHCS offers benefits because it helps hospitals to reduce costs, prevent contagiousinfections and give some emotional and psychological benefits to the patients. In this paper, a tactical and operational solution is proposed to the Home Health Care Routing and Scheduling Problem (HHCRSP) applied in the study case presented by Instituto Roosevelt (IR). IR manually defines the daily routes, and it generates the monthly staffing and workforce scheduling based on the HHCS head’s experience. This causes additional workload and human errors in routing assignments, staffing, and demand forecasting. This project integrates a single-objective Mixed Integer Linear Programming (MILP) model to tackle the monthly staffing and scheduling decisions, and a multi-objective MILP model to the scheduling and routing problem. The aim is to minimize the tactical costs associated with doctor's hiring and monthly assignment, and to minimize the operative costs and the gap differences between the maximum and minimum workload of the doctor’s routes assignment. Due to the high computation times of the routing MILP, a Non-dominated Sorting Genetic Algorithm (NSGA II) metaheuristic is applied. The final aim of the project is to design a tool that builds the daily route and the monthly staffing and workforce scheduling of the HHCS offered by the Instituto Roosevelt. Additionally, the tool will consider different stochastic components (demand and travel time) with a series of constraints associated with the Instituto Roosevelt’s case study. The methodology to deal with the stochastic parameters is through simulation and a Genetic Algorithm sim-heuristic that hybridizes the NSGA II with Monte Carlo Simulation. These methodologies and the MLPI’s proposed are carried out on a set of instances and their efficiencies are compared to test their performance. In the deterministic routing solution, the GA shows a competitive result by giving an average difference of 16% of the optimal costs and 0.4% on the optimal workload balance. In the stochastic routing component, it is evident that the results obtained by deterministic genetics with NSGA II are good, since approximately 70% of the time they obtain better results than the Institute's proposal. According to the literature review, the combined tactical and operational decisions with stochastic parameters have been little applied and discussed on HHCRSP (Home Health Care Routing and Scheduling Problem). That is the added value of this work.	spa
dc.description.abstractenglish	Due to several challenges in hospital service caused by the increasing demand for hospitalization, Home Health Care Service (HHCS) has become the best alternative for hospitals to provide a delivery service system that allows patients to be cared at their place of residence. The HHCS offers benefits because it helps hospitals to reduce costs, prevent contagiousinfections and give some emotional and psychological benefits to the patients. In this paper, a tactical and operational solution is proposed to the Home Health Care Routing and Scheduling Problem (HHCRSP) applied in the study case presented by Instituto Roosevelt (IR). IR manually defines the daily routes, and it generates the monthly staffing and workforce scheduling based on the HHCS head’s experience. This causes additional workload and human errors in routing assignments, staffing, and demand forecasting. This project integrates a single-objective Mixed Integer Linear Programming (MILP) model to tackle the monthly staffing and scheduling decisions, and a multi-objective MILP model to the scheduling and routing problem. The aim is to minimize the tactical costs associated with doctor's hiring and monthly assignment, and to minimize the operative costs and the gap differences between the maximum and minimum workload of the doctor’s routes assignment. Due to the high computation times of the routing MILP, a Non-dominated Sorting Genetic Algorithm (NSGA II) metaheuristic is applied. The final aim of the project is to design a tool that builds the daily route and the monthly staffing and workforce scheduling of the HHCS offered by the Instituto Roosevelt. Additionally, the tool will consider different stochastic components (demand and travel time) with a series of constraints associated with the Instituto Roosevelt’s case study. The methodology to deal with the stochastic parameters is through simulation and a Genetic Algorithm sim-heuristic that hybridizes the NSGA II with Monte Carlo Simulation. These methodologies and the MLPI’s proposed are carried out on a set of instances and their efficiencies are compared to test their performance. In the deterministic routing solution, the GA shows a competitive result by giving an average difference of 16% of the optimal costs and 0.4% on the optimal workload balance. In the stochastic routing component, it is evident that the results obtained by deterministic genetics with NSGA II are good, since approximately 70% of the time they obtain better results than the Institute's proposal. According to the literature review, the combined tactical and operational decisions with stochastic parameters have been little applied and discussed on HHCRSP (Home Health Care Routing and Scheduling Problem). That is the added value of this work.	spa
dc.description.degreelevel	Pregrado
dc.description.degreename	Ingeniero (a) Industrial
dc.format	PDF
dc.format.mimetype	application/pdf
dc.identifier.doi	https://doi.org/10.60794/vjq1-4k90
dc.identifier.instname	instname:Pontificia Universidad Javeriana
dc.identifier.reponame	reponame:Repositorio Institucional - Pontificia Universidad Javeriana
dc.identifier.repourl	repourl:https://repository.javeriana.edu.co
dc.identifier.uri	http://hdl.handle.net/10554/61507
dc.language.iso	spa
dc.publisher	Pontificia Universidad Javeriana
dc.publisher.faculty	Facultad de Ingeniería
dc.publisher.program	Ingeniería Industrial
dc.rights.accessrights	info:eu-repo/semantics/openAccess
dc.rights.coar	info:eu-repo/semantics/openAccess
dc.rights.licence	Atribución-NoComercial-SinDerivadas 4.0 Internacional
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dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	Problema de programación y ruteo de personal en servicios médicos domiciliarios
dc.subject	Ruteo
dc.subject	Asistencia médica a domicilio
dc.subject	Preventivo
dc.subject	Modelo matemático
dc.subject	Determinístico
dc.subject	Estocástico
dc.subject	Simulación
dc.subject	Optimización
dc.subject	Multi-objetivo
dc.subject	NSGA II
dc.subject.armarc	Ingeniería industrial - Tesis y disertaciones académicas
dc.subject.armarc	Enrutadores (Redes de computadores)	spa
dc.subject.armarc	Programación (Computadores electrónicos digitales)	spa
dc.subject.armarc	Atención médica ambulatoria	spa
dc.subject.keyword	HHCRSP
dc.subject.keyword	Routing
dc.subject.keyword	Home health care
dc.subject.keyword	Preventive
dc.subject.keyword	Mathematic model
dc.subject.keyword	Deterministic
dc.subject.keyword	Sthocastic
dc.subject.keyword	Simulation
dc.subject.keyword	Optimization
dc.subject.keyword	Multi-objective
dc.subject.keyword	NSGA II
dc.title	Home health care routing and scheduling problem: A preventive approach	spa
dc.type.coar	http://purl.org/coar/resource_type/c_7a1f
dc.type.driver	info:eu-repo/semantics/bachelorThesis
dc.type.hasversion	http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.local	Tesis/Trabajo de grado - Monografía - Pregrado