DocumentCode :
2224355
Title :
Method of Inequality-Based Multi-Objective Genetic Algorithm for Course Scheduling Model
Author :
Liu Chu-ling ; Peng Ping ; Xie Zan-fu ; Chen Chao-tian
Author_Institution :
Coll. of Comput. Sci., Guangdong Polytech. Normal Univ., Guangzhou, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
270
Lastpage :
273
Abstract :
The constraints, goals and difficulties in the course scheduling problem are discussed in this paper, and the course scheduling model based on method of inequality-based multi-objective genetic algorithm (MMGA) is proposed. The auxiliary performance index vector is introduced into the original multi-objective optimization problem, and a new method that guarantees the search in the "region of interest" through inequality transformation. The new method which makes up for the deficiencies in course scheduling with traditional genetic algorithm is a more practical form of algorithm, which describes the course scheduling problem much closer to the reality.
Keywords :
educational courses; genetic algorithms; scheduling; auxiliary performance index vector; course scheduling model; course scheduling problem; inequality transformation; inequality-based multiobjective genetic algorithm; Computer science; Education; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Optimization methods; Performance analysis; Processor scheduling; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
Type :
conf
DOI :
10.1109/ICISE.2009.738
Filename :
5455188
Link To Document :
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