Genetic Algorithm based Timetable Generating System (Case Study: Nurse Rostering Problem)

Abstract

Combinatorial problems are prominent in Artificial Intelligent and Operation Research. They can’t be solved in a given polynomial time with deterministic algorithm, also known as NP complete. Some researchers survey these problems as optimization problems and others examine as constraint satisfaction problems according to the techniques they used to implement. Many problems for instance frequency assignment, facility layout, vehicle routing, propositional logic satisfiablity, graph coloring, temporal and spatial reasoning and also scheduling are in combinatorial nature. Nurse Rostering Problem (NRP) stands as a subclass of scheduling problem. A nurse roster is composed of duty shifts and respite of nurses working at a hospital. The excellent scheduling of nurses has impression on the superiority of healthcare, the employment of nurses, the progress of budgets and other nursing utilities. In this study, metaheuristics such as Genetic Algorithm and Tabu Search are applied to deal with NRP.