Memetic differential evolution algorithm for operating room scheduling

In this paper, we propose an efficient Memetic Differential Evolution Algorithm (MDEA) which combines the Differential Evolution Algorithm (DEA) and Variable Neighborhood Search (VNS) to solve the operating room scheduling. The later consists in assigning an operating room to the blocks and a starting time to each intervention which takes into account both the operating rooms and the recovery beds. It aims at minimizing the weighted overtime of the operating rooms and the penalizing function of the violation of the idle time between the interventions in the same time block. Computational results show that, the proposed MDEA is satisfactory in terms of solution quality when compared with other meta-heuristics.