Abstract
Considering the complete process of surgery including the preoperative and postoperative stages, multiple resource constraints involved and the integration of surgical upstream and downstream resources, surgery scheduling was described as an extended multi-resource constrained flexible job-shop scheduling problem and an optimization approach was proposed based on an improved ant colony algorithm. A resource selection rule and strategy of overtime judging and adjusting was designed, and the scheduling process with the ant colony algorithm was realized. The case study shows that the improved ant colony algorithm proposed in this paper achieved good results in shortening total time and allocating resources for surgery scheduling.
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Yin, J., Xiang, W. (2012). Ant Colony Algorithm for Surgery Scheduling Problem. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_24
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DOI: https://doi.org/10.1007/978-3-642-30976-2_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30975-5
Online ISBN: 978-3-642-30976-2
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