Abstract
Surgery generates the largest cost and revenue in the hospital. The quality of operation directly affects the level of patient satisfaction and economic benefit. This paper focuses on partitioning patients into different priorities according to the state of illness, an optimization model with the aim of maximizing customer satisfaction is established under the consideration of a three-dimensional parameter constraint related patients, operating rooms and medical staffs. An Genetic algorithm is proposed with two-dimensional 0-1 encoding for solving the surgery scheduling problem with the data derived from an upper first-class hospital, the experimental results show the efficiency of the model and algorithm.
This research is supported by the National Science Foundation of China (70625001 and 70721001), the Fundamental Research Funds for the central Universities of MOE (N090204001).
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Wang, Y., Tang, J., Qu, G. (2010). A Genetic Algorithm for Solving Patient- Priority- Based Elective Surgery Scheduling Problem. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_33
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DOI: https://doi.org/10.1007/978-3-642-15597-0_33
Publisher Name: Springer, Berlin, Heidelberg
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