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- W2955983325 abstract "Currently, Health Units in a large number of countries in the world present service demand that exceeds their real capacities. This problem causes the inevitable emergence of long waiting lists. The optimization of such waiting list is very challenging, due to the large number of resources that must be considered. This paper proposes a new model, based on a quantum-inspired evolutionary algorithm, to optimize the scheduling of for elective surgical procedures. The Quantum-Inspired Evolutionary Algorithm for Healthcare (QIEA-H) model, aims not only to designate the necessary resources to the patients in order to achieve the successful completion of the chirurgical procedure, but also to reduce the total time used to perform all surgeries and the number of surgeries out of term. For the validation of the proposed model, a waiting list of 2000 surgeries was created artificially and using a simulation tool also developed in this work. The model achieved a reduction in the time of all surgeries of up to 16.25% and the number of surgeries out of date of up to 13.04%." @default.
- W2955983325 created "2019-07-12" @default.
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- W2955983325 date "2019-07-13" @default.
- W2955983325 modified "2023-10-18" @default.
- W2955983325 title "Resource optimization for elective surgical procedures using quantum-inspired genetic algorithms" @default.
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- W2955983325 doi "https://doi.org/10.1145/3321707.3321786" @default.
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