Implementation of operating room scheduling with genetic algorithm

In this thesis, the problem of the most efficient use of the Operating Rooms (ORs) which one of the most important departments of hospitals, was tackled. 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 traditional methods based on mathematics. In addition, healthy results cannot be obtained by using numerical analysis 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, simulated annealing have emerged. In this thesis, the operating room scheduling problem is solved by the genetic algorithm, which is one of the most important meta-heuristic algorithms. C# programming language is preferred to provide visuality when coding the program. Furthermore, the effect and the importance of using the repair operator as an operator of the genetic algorithm in these types of problems were also investigated.