An Intelligent Approach to Surgery Scheduling

Khanna, Sankalp; Sattar, Abdul; Boyle, Justin; Hansen, David; Stantić, Bela

doi:10.1007/978-3-642-25920-3_39

Cited by 4 publications

(1 citation statement)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…proposta de Fei, Meskens e Chu (2010) tem como objetivo maximizar a utilização dos centros cirúrgicos, minimizando o custo de horas extras e o tempo de ociosidade dos recursos físicos (equipamentos, unidade cirúrgica). Os autores dividem o problema em duas trabalho deKhanna et al (2012) apresenta a aplicação da metodologia de sistemas multiagentes para a modelagem de problemas com compartilhamento de recursos, como é o caso do agendamento de cirurgias eletivas. Neste artigo discute-se os desafios da otimização em problemas complexos como este, além de propor técnicas inteligentes capazes de conduzir algoritmos heurísticos para o melhor planejamento e gestão da programação de cirurgias.…”

unclassified

O problema de sequenciamento de cirurgias eletivas: uma abordagem heurística por meio do método iterated local search

Cruz¹

View full text Add to dashboard Cite

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.

show abstract

unclassified

O problema de sequenciamento de cirurgias eletivas: uma abordagem heurística por meio do método iterated local search

Cruz¹

View full text Add to dashboard Cite

show abstract

Evaluating Incomplete DCOP Algorithms On Large-Scale Problems

Leite

Enembreck

2019

2019 International Joint Conference on Neural Networks (IJCNN)

View full text Add to dashboard Cite

Distributed Constraint Optimization Problems and Applications: A Survey

Fioretto¹,

Pontelli²,

Yeoh³

2018

jair

144

119

View full text Add to dashboard Cite

The field of multi-agent system (MAS) is an active area of research within artificial intelligence, with an increasingly important impact in industrial and other real-world applications. In a MAS, autonomous agents interact to pursue personal interests and/or to achieve common objectives. Distributed Constraint Optimization Problems (DCOPs) have emerged as a prominent agent model to govern the agents' autonomous behavior, where both algorithms and communication models are driven by the structure of the specific problem. During the last decade, several extensions to the DCOP model have been proposed to enable support of MAS in complex, real-time, and uncertain environments.This survey provides an overview of the DCOP model, offering a classification of its multiple extensions and addressing both resolution methods and applications that find a natural mapping within each class of DCOPs. The proposed classification suggests several future perspectives for DCOP extensions, and identifies challenges in the design of efficient resolution algorithms, possibly through the adaptation of strategies from different areas.

show abstract

An Intelligent Approach to Surgery Scheduling

Cited by 4 publications

References 18 publications

O problema de sequenciamento de cirurgias eletivas: uma abordagem heurística por meio do método iterated local search

O problema de sequenciamento de cirurgias eletivas: uma abordagem heurística por meio do método iterated local search

Evaluating Incomplete DCOP Algorithms On Large-Scale Problems

Distributed Constraint Optimization Problems and Applications: A Survey

Contact Info

Product

Resources

About