A memetic algorithm based on MOEA/D for the examination timetabling problem

被引：8
|
作者：
Lei, Yu [1 ]
Shi, Jiao [1 ]
Yan, Zhen [2 ]
机构：
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
[2] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Hubei, Peoples R China
来源：
SOFT COMPUTING | 2018年 / 22卷 / 05期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Uncapacitated examination timetabling problem; Multiobjective optimization; MOEA/D; Local search; MATCHING-BASED SELECTION; EVOLUTIONARY ALGORITHM;
D O I：
10.1007/s00500-017-2886-y
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1511 / 1523
页数：13
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