A fuzzy density analysis of subgroups by means of DNA oligonucleotides

Ikno Kim, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingChapter

    1 Citation (Scopus)

    Abstract

    In complicated industrial and organizational relationships between employees or workers, it is difficult to offer good opportunities for their psychological and skill growth, since our progressive information and industrial societies have created many menial tasks. Redesigning subgroups in a personnel network for work rotation is a method that organizes employees appropriately to address these types of problems. In this article, we focus on a fuzzy density analysis of subgroups where employees are connected via their relationships with fuzzy values. However, it becomes extremely hard to rearrange those employees when there are vast numbers of them, meaning it is an NP-hard problem. In the personnel network, all the possible cohesive subgroups can be detected by making the best use of DNA oligonucleotides, which is also applied as a method by which to rearrange employees via fuzzy values based on the results of a fuzzy density analysis.

    Original languageEnglish
    Title of host publicationStudies in Computational Intelligence
    Pages31-45
    Number of pages15
    Volume217
    DOIs
    Publication statusPublished - 2009

    Publication series

    NameStudies in Computational Intelligence
    Volume217
    ISSN (Print)1860949X

    ASJC Scopus subject areas

    • Artificial Intelligence

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  • Cite this

    Kim, I., & Watada, J. (2009). A fuzzy density analysis of subgroups by means of DNA oligonucleotides. In Studies in Computational Intelligence (Vol. 217, pp. 31-45). (Studies in Computational Intelligence; Vol. 217). https://doi.org/10.1007/978-3-642-01885-5_2