A memetic algorithm based on MOEA/D for the examination timetabling problem
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A memetic algorithm based on MOEA/D is presented to deal with the uncapacitated multiobjective examination timetabling problem in this paper. The examination timetabling problem is considered as a two-objective optimization problem in this paper, while it is modeled as a single-objective optimization problem generally. The framework of a multiobjective evolutionary algorithm with decomposition (MOEA/D) is first employed to guide the evolutionary process. Two special local search operators are designed to find better individuals. The proposed algorithm is tested on 11 benchmark examination timetabling instances. Experimental results prove that the proposed algorithm can produce a promising set of nondominated solutions for each examination timetabling instance.
KeywordsUncapacitated examination timetabling problem Multiobjective optimization MOEA/D Local search
This work is supported by the National Natural Science Foundation of China. (Grant Nos. 61603299 and 61602385) and China Postdoctoral Science Foundation (2017M613204).
Compliance with ethical standards
Conflict of interest
Yu Lei and Jiao Shi declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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