O problema de sequenciamento de cirurgias eletivas:uma abordagem heurística por meio do método iterated local search
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Tipo de produção
Dissertação
Data
2016
Autores
Cruz, R. C.
Orientador
Chang Junior, João
Periódico
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Citação
CRUZ, R. C. O problema de sequenciamento de cirurgias eletivas: uma abordagem heurística por meio do método iterated local search. 2016. 97 f. Dissertação (Mestrado em Engenharia Mecânica) - Centro Universitário FEI, São Bernardo do Campo, 2016. Disponível em: . Acesso em: 8 out. 2018.
Texto completo (DOI)
Palavras-chave
Cirurgia,Algoritmos,Sequenciamento de cirurgias eletivas,Métodos heurísticos
Resumo
O presente trabalho tem seu foco no Problema de Sequenciamento de Cirurgias Eletivas. Este problema consiste em alocar um conjunto de cirurgias eletivas ao longo da agenda de programação levando em consideração os recursos hospitalares disponíveis, sendo eles: salas de cirurgias, equipamentos médicos, cirurgiões, enfermeiros, anestesistas, equipes de higienização, entre outros. O objetivo é apresentar a programação de cirurgias eletivas com o menor tempo total de processamento possível. Pelo fato de os recursos hospitalares serem na maioria das vezes escassos e de alto custo, o compartilhamento deles e a alocação de cirurgias de forma sistêmica se fazem necessários, uma vez que resolvendo este problema é possível diminuir o tempo total de execução das operações, aumentar o número de cirurgias realizadas e diminuir o tempo de espera dos pacientes. Para resolver este complexo problema combinatório, caracterizado como NP-difícil, propõe-se o algoritmo heurístico computacional denominado ESSILS (do inglês, Elective Surgery Scheduling Iterated Local Search), o qual combina as metaheurísticas Iterated Local Search, Variable Neighborhood Descent e Busca Tabu. Estudos bibliográficos comprovaram que a utilização de técnicas computacionais para a solução deste problema é muito pouco abordada no Brasil. À vista disso, pretende-se também que este trabalho auxilie os tomadores de decisão na tarefa de programar cirurgias eletivas nos mais diversos hospitais do país. Esta proposta foi testada em problemas-teste consagrados da literatura e também em problemas reais de um hospital de grande porte da cidade de São Paulo (Brasil), mostrando-se eficaz em relação às demais abordagens existentes.
The present work focuses on the Elective Surgeries Scheduling Problem. This problem consists to allocate a set of elective surgeries along the scheduling program considering the available hospital resources, namely: operating rooms, medical equipment, surgeons, nurses, anesthetists, cleaning teams, among others. The purpose is to present the elective surgeries scheduling with the lowest possible processing time. Due the hospital resources are, in most cases, scarce as well as expensive, sharing them and allocating surgeries in a systemic way are necessary, since solving this problem is possible to reduce the total execution time, increase the number of scheduled surgeries and reduce the waiting time for patients. To solve this complex combinatorial problem, characterized as NP-hard, it is proposed the computational heuristic algorithm called ESSILS (Elective Surgery Scheduling Iterated Local Search), which combines the metaheuristics Iterated Local Search, Variable Neighborhood Descent and Tabu Search. Published studies have shown that the use of computational techniques for this kind of problem is rarely addressed in Brazil. In view of this, this work also intends to contribute with decision makers during the elective surgeries scheduling activities in many hospitals of the country. This proposal was tested in benchmark problems of literature and also real problems of a large hospital in São Paulo (Brazil), being effective in relation to other existing approaches.
The present work focuses on the Elective Surgeries Scheduling Problem. This problem consists to allocate a set of elective surgeries along the scheduling program considering the available hospital resources, namely: operating rooms, medical equipment, surgeons, nurses, anesthetists, cleaning teams, among others. The purpose is to present the elective surgeries scheduling with the lowest possible processing time. Due the hospital resources are, in most cases, scarce as well as expensive, sharing them and allocating surgeries in a systemic way are necessary, since solving this problem is possible to reduce the total execution time, increase the number of scheduled surgeries and reduce the waiting time for patients. To solve this complex combinatorial problem, characterized as NP-hard, it is proposed the computational heuristic algorithm called ESSILS (Elective Surgery Scheduling Iterated Local Search), which combines the metaheuristics Iterated Local Search, Variable Neighborhood Descent and Tabu Search. Published studies have shown that the use of computational techniques for this kind of problem is rarely addressed in Brazil. In view of this, this work also intends to contribute with decision makers during the elective surgeries scheduling activities in many hospitals of the country. This proposal was tested in benchmark problems of literature and also real problems of a large hospital in São Paulo (Brazil), being effective in relation to other existing approaches.