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Method of Inequality-Based Multi-Objective Genetic Algorithm for Course Scheduling Model

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4 Author(s)
Liu Chu-ling ; Coll. of Comput. Sci., Guangdong Polytech. Normal Univ., Guangzhou, China ; Peng Ping ; Xie Zan-fu ; Chen Chao-tian

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.

Published in:

Information Science and Engineering (ICISE), 2009 1st International Conference on

Date of Conference:

26-28 Dec. 2009