A particle swarm optimization algorithm on the surgery scheduling problem with downstream process

This paper focuses on generating an optimal surgery schedule of elective-patients in multiple operating theatres, which considering the intra-operative care and recovery phases. We try to determine the surgery sequence and location. With regard to the downstream process, recovery room, the problem is modeled as a hybrid integer program with the objective of minimizing the operating costs of hospital, which includes operating rooms´ fixed costs, operating rooms´ overtime costs and recovery costs. A discrete particle swarm optimization algorithm combined with heuristic rules is proposed. We text our approach with realistic data, the results show the algorithm we present basically reached the same level of CPLEX, while the computation time is far less than CPLEX. Additionally, the approach can find the optimized number of daily opening operating rooms and recovery beds through varying parameters in the experiment, which give management insights to hospital and reduce the daily operating cost.