Title :
HGGASA: An Annealing Grouping Genetic Algorithm for Finding Feasible Timetables
Author :
Najafi-Ardabili, A. ; Qarouni-Fard, Danial ; Andalibizadeh, Mohamad-reza ; Ghorbani, Ooldooz ; Sheikhaei, Mohammad-Sadegh ; Mohammadzadeh, Javad
Author_Institution :
Dept. of Comput. Sci., Ferdowsi Univ., Mashad, Iran
Abstract :
Timetabling is a well-known NP-complete constraint satisfaction problem (CSP) that has been widely studied in the past. In this paper we adopt a modified Genetic Algorithm, better know as Grouping GA and tweaked to suit grouping problems. GGA is further combined with Simulated Annealing (HGGASA) to implement the notion of an acceptance function and improve the performance rate of the algorithm. The results demonstrate a better convergence rate for HGGASA, but not uniformly.
Keywords :
computational complexity; constraint theory; genetic algorithms; operations research; simulated annealing; HGGASA; NP-complete constraint satisfaction problem; feasible timetables; grouping genetic algorithm; simulated annealing; Biological cells; Computational modeling; Computer science; Convergence; Encoding; Evolutionary computation; Genetic algorithms; Genetic engineering; Java; Simulated annealing; Grouping Genetic Algorithm; Simulated Annealing; Soft Computing; Timetable;
Conference_Titel :
Innovations in Information Technology, 2007. IIT '07. 4th International Conference on
Conference_Location :
Dubai
Print_ISBN :
978-1-4244-1840-4
Electronic_ISBN :
978-1-4244-1841-1
DOI :
10.1109/IIT.2007.4430501
