Decision support for proposal grouping : A hybrid approach using knowledge rule and genetic algorithm

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

21 Scopus Citations
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Author(s)

  • Zhi-Ping Fan
  • Yuan Chen
  • Jian Ma
  • Yan Zhu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1004-1013
Journal / PublicationExpert Systems with Applications
Volume36
Issue number2 PART 1
Publication statusPublished - Mar 2009

Abstract

Proposal grouping is a special procedure in the sponsorship process for research projects. In practice, it is conducted to simplify the following procedure of reviewer assignment. As the proposals grow, this procedure becomes complex. Practical managers spend an increasing amount of time struggling for identifying valid proposals, classifying proposals and partitioning proposals into groups as well as maintaining some control over the quality and composition of the resulting groups. This paper proposes an approach for proposal grouping, in which knowledge rules are designed to deal with proposal identification and proposal classification, and the genetic algorithm is developed to search for the expected groupings. In addition, a corresponding system is designed and developed to support the proposed approach. Compared to the previous manual grouping, the proposed approach significantly reduces the time required for grouping, ensures more diverse group composition, and increases overall grouping quality. © 2007 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Decision support system, Genetic algorithm, Knowledge rule, Project management