A hybrid imperialist competitive algorithm for the outpatient scheduling problem with switching and preparation times

In recent years, outpatient scheduling problem has attracted much attention. This paper considers the outpatient scheduling problem as an extension of the flexible job shop scheduling problem (FJSP), where the patient is considered as a job. Then, to solve the outpatient scheduling problem, a hybrid imperialist competitive algorithm (HICA) is proposed. In the proposed algorithm, the simulated annealing (SA) algorithm and estimation of distribution algorithm (EDA) are embedded to improve the quality of the solution. Furthermore, the two realistic constraints, i.e., switching time and preparation time of patients are also considered to make the problem closer to the reality. Finally, to verify the performance of the proposed HICA, different outpatient scheduling problem instances are randomly generated and used for simulation tests. Four efficient algorithms, including imperialist competitive algorithm (ICA), improved genetic algorithm (IGA), EDA, and modified artificial immune algorithm (MAIA), are selected for detailed comparisons. The simulation results confirm that the proposed algorithm can solve the outpatient scheduling problem with high efficiency.