DocumentCode :
2354334
Title :
University Time Table Scheduling Using Genetic Artificial Immune Network
Author :
Bhaduri, Antariksha
fYear :
2009
fDate :
27-28 Oct. 2009
Firstpage :
289
Lastpage :
292
Abstract :
Scheduling is one of the important tasks encountered in real life situations. Various scheduling problems are present, like personnel scheduling, production scheduling, education time table scheduling etc. Educational time table scheduling is a difficult task because of the many constraints that are needed to be satisfied in order to get a feasible solution. Education time table scheduling problem is known to be NP hard. Hence, evolutionary techniques have been used to solve the time table scheduling problem. Methodologies like Genetic Algorithms (GAs), Evolutionary Algorithms (EAs) etc have been used with mixed success. In this paper, we have reviewed the problem of educational time table scheduling and solving it with genetic algorithm. We have further solved the problem with a memetic hybrid algorithm, genetic artificial immune network (GAIN) and compare the result with that obtained from GA. Results show that GAIN is able to reach the optimal feasible solution faster than that of GA.
Keywords :
artificial immune systems; educational administrative data processing; genetic algorithms; educational time table scheduling; evolutionary technique; genetic artificial immune network; memetic hybrid algorithm; university time table scheduling; Communications technology; Computer networks; Constraint optimization; Educational products; Genetic algorithms; Immune system; Personnel; Processor scheduling; Production; Scheduling algorithm; Educational Time tabling; Genetic Algorithm; Genetic Artificial Immune Network; Memetic Algorithm; Scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
Conference_Location :
Kottayam, Kerala
Print_ISBN :
978-1-4244-5104-3
Electronic_ISBN :
978-0-7695-3845-7
Type :
conf
DOI :
10.1109/ARTCom.2009.117
Filename :
5329471
Link To Document :
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