@inproceedings{ee318e6e7f9448a78d74e06aeb4dd377,
title = "Grouping genetic algorithms: An exploratory study",
abstract = "Grouping problems are an important class of computational problems where the objective is to group, cluster or partition members of a set into desired sub sets. The grouping genetic algorithm is an extension of genetic algorithm that is heavily modified to model the structure of grouping problems. Since its inception, grouping genetic algorithms has been applied to several types of grouping problems. This paper presents an exploratory and chronological review of the grouping genetic algorithm approach. First, a survey of articles on grouping genetic algorithm approaches and its applications is presented. Second, a chronological review and analysis of research activities on the grouping genetic algorithm approach is presented. Third and finally, future trends and further research prospects are visualized and outlined.",
keywords = "Chronological review, Exploratory study, Genetic algorithms, Grouping, Grouping genetic algorithms",
author = "Michael Mutingi and Charles Mbohwa and Harmony Musiyarira",
note = "Publisher Copyright: {\textcopyright} Copyright International Association of Engineers.; 2017 World Congress on Engineering and Computer Science, WCECS 2017 ; Conference date: 25-10-2017 Through 27-10-2017",
year = "2017",
language = "English",
isbn = "9789881404756",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "490--494",
editor = "Ao, {S. I.} and Grundfest, {W. S.} and Craig Douglas",
booktitle = "Proceedings of the World Congress on Engineering and Computer Science 2017, WCECS 2017",
}