Abstract: In order to solve the scheduling problem of batch emergency surgery in urban emergency rescue, and considering deteriorating effect for the duration of operation and success rate of saving life brought by long-term continuous operations, a three-stage batch surgery scheduling model is proposed, regarding emergency surgery scheduling as a flow-shop scheduling problem with parallel machines. Then the model is solved and tested by the improved moth-flame optimization (IMFO) and empirical evidence, respectively. In order to verify the performance of the algorithm, the classical moth fire suppression algorithm (MFO), particle swarm optimization algorithm (PSO) and cuckoo search algorithm (CS) are compared. It can be seen that IMFO is the minimum in the results of mean value of each algorithm after 20 simulations. The three treatment stages of the scheduling scheme given by the scheduling model are coherent in time dimension. The experimental results show that IMFO can solve the model well and get good results.

Key words: emergency, surgical scheduling, fatigue effect, moth-flame optimization, chaotic disturbance