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Planeamento de rotas dinâmicas para a prestação de cuidados respiratórios domiciliários
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A prestação de cuidados de saúde no domicílio é um serviço cada vez mais relevante e
exigente, que cresceu muito nos últimos anos devido à evolução tecnológica e à atual crise
pandémica. Na prestação deste serviço estão envolvidos vários agentes que concentram os seus
esforços no bem-estar e qualidade de vida dos seus pacientes com tratamentos prescritos.
Existe, no entanto, um agente que, devido à função que desempenha junto dos pacientes,
desenvolve uma relação de proximidade e intimidade que se revela ser um critério relevante na
análise da qualidade e valor dos serviços prestados. Este agente é constituído pelas empresas
especializadas com equipas de técnicos que se deslocam até ao domicílio dos pacientes que
necessitam dos vários tipos de serviços disponíveis. O caso em estudo é baseado em dados reais de uma empresa que presta serviços de cuidados respiratórios domiciliários. No início do dia existem serviços que já se encontram agendados nas rotas dos técnicos disponíveis. Este planeamento é realizado no dia anterior sendo assegurada disponibilidade para que possam ser inseridos novos pedidos que chegam ao longo do dia. A empresa deve satisfazer em tempo útil cada novo pedido, minimizando o número total de horas
de trabalho. Trata-se de um problema de rotas dinâmico.Para encontrar soluções admissíveis para o problema foram desenvolvidos e implementados dois algoritmos em Python. No primeiro, partindo-se do conjunto inicial das rotas planeadas, à medida que vão surgindo novos pedidos ao longo do dia, aplica-se a heurística de inserção de menor custo com o objetivo de integrar os novos pedidos nessas rotas. O segundo, com o objetivo
de melhorar a solução obtida pela heurística de menor custo de inserção, consiste em aplicar uma
heurística 2-optimal sempre que inserido um novo pedido numa rota. Os testes computacionais são realizados considerando dois cenários que variam na distribuição temporal da chegada de novos pedidos ao longo do dia e um cenário em que se consideram dois turnos de trabalho no horário laboral dos técnicos. É realizada uma análise dos resultados obtidos em termos percentuais comparando as soluções dos diferentes cenários com a solução obtida considerando os dados reais fornecidos pela empresa.
Home healthcare is an increasingly relevant and demanding service, which has grown in recent years due to technological developments and the current pandemic crisis. In the provision of this service, several agents are involved, who focus their efforts on the well-being and quality of life of their patients with prescribed treatments.There is, however, one agent who, due to the role he plays with the patients, develops a relationship of proximity and intimacy that proves to be a relevant criterion in the analysis of the quality and value of the services provided. This agent is made up of specialized companies with teams of technicians who travel to the patient’s homes who need the various types of services available. The case under study is based on real data from a company that provides home respiratory care services. At the beginning of the day there are services that have already been scheduled on the available technicians’ routes. This planning is done the day before, and availability is ensured to attend new requests that come up during the day. The company must satisfy each new request on time, minimizing the total number of working hours. This problem is classified as a dynamic routing problem. To find feasible solutions to the problem two algorithms were developed and implemented in Python. In the first one, starting from the initial set of planned routes, the cheapest insertion heuristic is applied as new requests arise throughout the day, with the objective of integrating the new requests into those routes. The second one, with the goal of improving the solution obtained by the cheapest insertion heuristic, consists in applying a 2-optimal heuristic whenever a new request is inserted in a route. The computational tests are performed considering two scenarios that vary in the temporal distribution of the arrival of new requests throughout the day and a third scenario in which two shifts are considered. An analysis of the results obtained in percentage terms is performed comparing the solutions of the different scenarios with the solution obtained considering the actual data provided by the company.
Home healthcare is an increasingly relevant and demanding service, which has grown in recent years due to technological developments and the current pandemic crisis. In the provision of this service, several agents are involved, who focus their efforts on the well-being and quality of life of their patients with prescribed treatments.There is, however, one agent who, due to the role he plays with the patients, develops a relationship of proximity and intimacy that proves to be a relevant criterion in the analysis of the quality and value of the services provided. This agent is made up of specialized companies with teams of technicians who travel to the patient’s homes who need the various types of services available. The case under study is based on real data from a company that provides home respiratory care services. At the beginning of the day there are services that have already been scheduled on the available technicians’ routes. This planning is done the day before, and availability is ensured to attend new requests that come up during the day. The company must satisfy each new request on time, minimizing the total number of working hours. This problem is classified as a dynamic routing problem. To find feasible solutions to the problem two algorithms were developed and implemented in Python. In the first one, starting from the initial set of planned routes, the cheapest insertion heuristic is applied as new requests arise throughout the day, with the objective of integrating the new requests into those routes. The second one, with the goal of improving the solution obtained by the cheapest insertion heuristic, consists in applying a 2-optimal heuristic whenever a new request is inserted in a route. The computational tests are performed considering two scenarios that vary in the temporal distribution of the arrival of new requests throughout the day and a third scenario in which two shifts are considered. An analysis of the results obtained in percentage terms is performed comparing the solutions of the different scenarios with the solution obtained considering the actual data provided by the company.
Descrição
Trabalho de projeto de mestrado, Matemática Aplicada à Economia e Gestão, Universidade de Lisboa, Faculdade de Ciências, 2022
Palavras-chave
cuidados respiratórios domiciliários problema de rotas para veículos dinâmico heurística de inserção de menor custo heurística 2-optimal Teses de mestrado - 2022