Solving Operating Room Scheduling Problem Using Artificial Bee Colony Algorithm

Abstract

Many healthcare institutions are interested in reducing costs and in maintaining a good quality of care. The operating room department is typically one of the most costly units in a hospital. Hospital managers are always interested in finding effective ways of using operating rooms to minimize operating costs. In this research, we study the operating room scheduling problem. We consider the use of a weekly surgery schedule with an open scheduling strategy that takes into account the availabilities of surgeons and operating rooms. The objective is to minimize the total operating cost while maximizing the utilization of the operating rooms but also minimizing overtime use. A revised mathematical model is proposed that can provide optimal solutions for a surgery size up to 110 surgical cases. Next, two modified heuristics, based on the earliest due date (EDD) and longest processing time (LPT) rules, are proposed to quickly find feasible solutions to the studied problem. Finally, an artificial bee colony (ABC) algorithm that incorporates the initial solutions, a recovery scheme, local search schemes, and an elitism strategy is proposed. The computational results show that, for a surgery size between 40 and 100 surgical cases, the ABC algorithm found optimal solutions to all of the tested problems. For surgery sizes larger than 110 surgical cases, the ABC algorithm performed significantly better than the two proposed heuristics. The computational results indicate that the proposed ABC is promising and capable of solving large problems.