Title :
Adaptive Steady State Genetic Algorithm for scheduling university exams
Author :
Alsharafat, Wafa Slaibi ; AlSharafat, Mohammad Slaibi
Author_Institution :
Prince Hussein Bin Abdullah Coll. for IT, Al Al-Bayt Univ., Mafraq, Jordan
Abstract :
Scheduling exams timetable, first and second exams, for large number of courses within Al Al-Bayt university departments is a complex problem since it has to be solved by using traditional method, manually by hands. In addition, it takes several days of iterative work by taking feedback from student. We describe an effective solution to solve this problem by using different form of Genetic Algorithm; Steady State Genetic algorithm(SSGA), Enhanced Steady State Genetic Algorithm(ESSGA), and Simple Genetic Algorithm(SGA). After performing a set of tests using real student data from several departments, we found that the ESSGA gains better timetable than other methods.
Keywords :
adaptive scheduling; educational institutions; genetic algorithms; Al Al Bayt university department; adaptive steady state genetic algorithm; enhanced steady state genetic algorithm; exams timetable; simple genetic algorithm; university exam scheduling; Artificial intelligence; Biological cells; Fuzzy logic; Genetic algorithms; Genetic mutations; Information technology; Iterative algorithms; Processor scheduling; Scheduling algorithm; Steady-state; ESSGA; Genetic algorithms; SSGA; Scheduling;
Conference_Titel :
Networking and Information Technology (ICNIT), 2010 International Conference on
Conference_Location :
Manila
Print_ISBN :
978-1-4244-7579-7
Electronic_ISBN :
978-1-4244-7578-0
DOI :
10.1109/ICNIT.2010.5508555