Ant colony algorithm for surgery scheduling problem

Authors:
Jiao Yin;Wei Xiang
Affiliations:
Faculty of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, P.R. China;Faculty of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, P.R. China
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2012

Citing 4
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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.