A hybrid grouping genetic algorithm for reviewer group construction problem

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

25 Scopus Citations
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Author(s)

  • Yuan Chen
  • Zhi-Ping Fan
  • Jian Ma
  • Shuo Zeng

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)2401-2411
Journal / PublicationExpert Systems with Applications
Volume38
Issue number3
Publication statusPublished - Mar 2011

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; Zeng, Shuo.

In: Expert Systems with Applications, Vol. 38, No. 3, 03.2011, p. 2401-2411.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review