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Desenvolvimento e aplicação de uma meta-heurística ao Home Health Care Problem
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Nos últimos anos tem-se assistido a um crescimento na percentagem de população idosa,
o que provocou um aumento na procura de cuidados ao domicílio. Como tal, é necessário
haver um planeamento eficiente, através da otimização do uso dos recursos, humanos e
materiais, bem como das rotas.
O objetivo desta dissertação é desenvolver um algoritmo para melhorar o planeamento
das rotas dos cuidados ao domicílio, auxiliando os prestadores de serviço (caregivers). A
otimização foca na minimização do tempo de viagem. O modelo é uma extensão do Vehicle
Routing Problem com janelas temporais, sincronização (quando 2 equipas de um caregiver
se encontram ao mesmo tempo para realizar um serviço que necessita de dois caregivers),
caregivers sem skills, para um horizonte temporal de um dia e com um tempo de trabalho
diário máximo de 480 minutos por equipa.
De modo a atingir o objetivo, foi aplicado o Biased Random Key Genetic Algorithm
(BRKGA), o qual é uma extensão do Genetic Algorithm (GA).
Para a obtenção dos resultados foi utilizado uma instância de teste com 75 clientes.
Para realizar os serviços estão à disposição 15 caregivers, entre os quais poderão ser for-
madas até oito combinações de equipas. As equipas são formadas por equipas de dois
caregivers e equipas de um caregiver. Um objetivo adicional é o de encontrar a melhor
combinação de equipas para o problema.
In the recent years we have seen a growth of the elderly population percentage, which has caused an increase in demand for home care support. As such, there is a need for efficient planning, by optimizing the use of human and material resources, as well as routes. The goal of this dissertation is to develop an algorithm to improve the planning of home care routes by the caregivers. The optimization focuses on minimizing travel time. The model is an extension of the Vehicle Routing Problem with time windows, synchronization (when two teams of one caregiver meet at the same time do perform a service that needs two caregivers), caregivers without skills, for a time horizon of one day and with a maximum daily working time of 480 minutes per team. In order to achieve the goal, the Biased Random Key Genetic Algorithm (BRKGA) was applied, which is an extension of the Genetic Algorithm (GA). A test instance with 75 clients was used to obtain the results. To perform the services 15 caregivers are available, from which can be formed up to eight team combinations. The teams are made up of teams of two caregivers and teams of one caregiver. An additional goal is to find the best combination of teams for the problem.
In the recent years we have seen a growth of the elderly population percentage, which has caused an increase in demand for home care support. As such, there is a need for efficient planning, by optimizing the use of human and material resources, as well as routes. The goal of this dissertation is to develop an algorithm to improve the planning of home care routes by the caregivers. The optimization focuses on minimizing travel time. The model is an extension of the Vehicle Routing Problem with time windows, synchronization (when two teams of one caregiver meet at the same time do perform a service that needs two caregivers), caregivers without skills, for a time horizon of one day and with a maximum daily working time of 480 minutes per team. In order to achieve the goal, the Biased Random Key Genetic Algorithm (BRKGA) was applied, which is an extension of the Genetic Algorithm (GA). A test instance with 75 clients was used to obtain the results. To perform the services 15 caregivers are available, from which can be formed up to eight team combinations. The teams are made up of teams of two caregivers and teams of one caregiver. An additional goal is to find the best combination of teams for the problem.
Descrição
Palavras-chave
Home Health Care Roteamento e Escalonamento Meta heurística Biased Random Key Genetic Algorithm Sincronização