A hybrid grouping genetic algorithm for reviewer group construction problem
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 2401-2411 |
Journal / Publication | Expert Systems with Applications |
Volume | 38 |
Issue number | 3 |
Publication status | Published - Mar 2011 |
Link(s)
Abstract
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. © 2010 Elsevier Ltd. All rights reserved.
Research Area(s)
- Grouping genetic algorithm, Heuristics, Hybrid genetic algorithm, OR in government, Reviewer group construction
Citation Format(s)
A hybrid grouping genetic algorithm for reviewer group construction problem. / Chen, Yuan; Fan, Zhi-Ping; Ma, Jian et al.
In: Expert Systems with Applications, Vol. 38, No. 3, 03.2011, p. 2401-2411.
In: Expert Systems with Applications, Vol. 38, No. 3, 03.2011, p. 2401-2411.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review