Title :
A mixed integer programming model for Bed planning considering stochastic length of stay
Author :
Xu Lei ; Li Na ; Yu Xin ; Mo Fan
Author_Institution :
Ind. Eng., Shanghai Jiaotong Univ., Shanghai, China
Abstract :
In this paper, we study hospital bed planning problem for a gynecological ward in China. We first proposed a mixed integer programming (MIP) model considering deterministic length of stay (LOS) to assign patients to available beds. Since statistical analysis of empirical hospitalization data reveals that variance of inpatient´s LOS is significant. Therefore, based on the deterministic LOS model we further proposed a MIP model taking stochastic LOS into consideration. Both models could be solved by standard linear programming solver CPLEX. Numerical experiments of bed assignment results comparison between the two proposed models are presented. The result shows stochastic LOS model can generate better bed planning solutions with lower potential schedule conflict cost.
Keywords :
data analysis; health care; hospitals; integer programming; linear programming; planning (artificial intelligence); statistical analysis; stochastic processes; CPLEX; China; MIP model; bed assignment; deterministic LOS model; empirical hospitalization data; gynecological ward; hospital bed planning problem; mixed integer programming model; patient assignment; standard linear programming solver; statistical analysis; stochastic LOS model; stochastic length-of-stay; Hospitals; Numerical models; Pathology; Schedules; Stochastic processes; Surgery; bed planning; mixed integer programming; stochastic LOS;
Conference_Titel :
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
Conference_Location :
Taipei
DOI :
10.1109/CoASE.2014.6899456