Dynamic Surgery Scheduling Based on an Improved Genetic Algorithm | Zendy

Bingbing Zhang | Zendy; Qiang Su | Zendy

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Dynamic Surgery Scheduling Based on an Improved Genetic Algorithm

Author(s) -

Bingbing Zhang,

Qiang Su

Publication year - 2021

Publication title -

journal of healthcare engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.509

H-Index - 29

eISSN - 2040-2309

pISSN - 2040-2295

DOI - 10.1155/2021/1559050

Subject(s) - computer science , dynamic priority scheduling , scheduling (production processes) , dynamic programming , mathematical optimization , genetic algorithm , job shop scheduling , algorithm , operations research , mathematics , machine learning , schedule , operating system

We formulated a new stochastic programming formulation to solve the dynamic scheduling problem in a given set of elective surgeries in the day of operation. The problem is complicated by the fact that the exact surgery durations are not known in advance. Elective surgeries could be performed in parallel in a subset of operating rooms. The appointment times and assignments of surgeries were planned by an experienced nurses in advance. We present a mathematical model to capture the nature of dynamic scheduling problem. We propose an efficient solution based on an improved genetic algorithm (IGA). Our numerical results showed that dynamic scheduling with the IGA improves the resource utilization as measured by surgeon waiting time and operation room idle time.

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