A hybrid grouping genetic algorithm for reviewer group construction problem

被引:24
作者
Chen, Yuan [3 ]
Fan, Zhi-Ping [1 ]
Ma, Jian [2 ]
Zeng, Shuo [4 ]
机构
[1] Northeastern Univ, Sch Business Adm, Dept Management Sci & Engn, Shenyang, Peoples R China
[2] City Univ Hong Kong, Dept Informat Syst, Kowloon, Hong Kong, Peoples R China
[3] Shanghai Univ Finance & Econ, Dept Informat Management & Engn, Shanghai, Peoples R China
[4] Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
关键词
OR in government; Reviewer group construction; Hybrid genetic algorithm; Grouping genetic algorithm; Heuristics; GROUP DECISION-MAKING; ASSIGNING STUDENTS;
D O I
10.1016/j.eswa.2010.08.029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is a common task to construct the reviewer group with diverse background between reviewers. This task is complicated considering the multiple criteria and sizable reviewers and groups. However, it has not been clearly addressed in the current studies. This paper investigates this problem and proposes a solution approach. In our study, this problem is firstly formulated as an integrated model that covers the situations of different group number and group size. Then, considering the computational difficulties of solving this model, the grouping genetic algorithm hybridizing the local neighborhood search heuristic is proposed. In the grouping genetic algorithm, the initialization, crossover and mutation are designed according to our problem's characteristics. Extensive numerical experiments show that the proposed algorithm is computationally efficient. Moreover, the application of the proposed algorithm on a case from NSFC also indicates its effectiveness for practical problems. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2401 / 2411
页数:11
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