Timucin, TunahanBirogul, Serdar2021-12-012021-12-012020978-3-030-36178-5; 978-3-030-36177-82367-4512https://doi.org/10.1007/978-3-030-36178-5_20https://hdl.handle.net/20.500.12684/10207International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME) -- APR 20-22, 2019 -- Antalya, TURKEYIn this paper, the problem of the most efficient use of the Operating Rooms (ORs) which one of the most important departments of hospitals, was tackled. Efficient use of operating rooms is a scheduling problem with many constraints. This type of problem is defined as NP-Hard. Complex problems involving multiple constraints are defined as NP-Hard type problems. As the NP-Hard type problem does not consist of polynomial values, the solution of such problems becomes complicated. Such problems cannot be solved by classical mathematical methods. For the solution of NP-Hard type problems which have high level of complexity and many constraints, heuristic and meta-heuristic algorithms such as Genetic Algorithm (GA), tabu search algorithm, simulated annealing algorithm and partical swarm optimization algorithm have emerged. In this paper, the operating room scheduling problem is solved by the genetic algorithm. When coding the program, the C# programming language was preferred because of the visual advantages and user-friendliness of the language.en10.1007/978-3-030-36178-5_20info:eu-repo/semantics/closedAccessOperating Room SchedulingGenetic AlgorithmConstrained optimizationConference Object432522652-s2.0-85083427078WOS:000678771000020Q3N/A