2026-10-25T03:03:16Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/3558 2021-12-13T03:36:33Z 1582963302567:1597824273898 user-ucsy

Genetic Algorithm based Timetable Generating System (Case Study: Nurse Rostering Problem) Pyae, Khaing Hsu Tun, Khin Nwe Ni Combinatorial problems are prominent inArtificial Intelligent and Operation Research. Theycan’t be solved in a given polynomial time withdeterministic algorithm, also known as NP complete.Some researchers survey these problems asoptimization problems and others examine asconstraint satisfaction problems according to thetechniques they used to implement. Many problemsfor instance frequency assignment, facility layout,vehicle routing, propositional logic satisfiablity,graph coloring, temporal and spatial reasoning andalso scheduling are in combinatorial nature. NurseRostering Problem (NRP) stands as a subclass ofscheduling problem. A nurse roster is composed ofduty shifts and respite of nurses working at ahospital. The excellent scheduling of nurses hasimpression on the superiority of healthcare, theemployment of nurses, the progress of budgets andother nursing utilities. In this study, metaheuristicssuch as Genetic Algorithm and Tabu Search areapplied to deal with NRP. 2010-12-16 http://hdl.handle.net/20.500.12678/0000003558 https://meral.edu.mm/records/3558