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Ant Colony Algorithm for Surgery Scheduling Problem

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7331))

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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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© 2012 Springer-Verlag Berlin Heidelberg

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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

  • eBook Packages: Computer ScienceComputer Science (R0)

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