TY - GEN
T1 - Analysing the density of subgroups in valued relationships based on DNA computing
AU - Kim, Ikno
AU - Jeng, Don Jyh Fu
AU - Watada, Junzo
PY - 2006
Y1 - 2006
N2 - One method for enhancing the quality of work life for companies or other organisations is to rearrange employees by detecting and analysing employees' close interpersonal relationships based on business implications. Although human resource managers can use various methods to enhance the quality of work life, one of the most widely used and effective methods is job rotation. In this paper, we select a model of a workplace where employees in a variety of job functions are sharing tasks, information, etc. through close interpersonal relationships, and we suppose a personnel network which contains strong terms of mutual understanding. However, with a huge number of employees it becomes extremely difficult to find the maximum clique of employees for rearrangement, meaning this is NP-hard. Therefore, we employ DNA computing, also known as molecular computation, to this rearranging problem. The goal of this paper is to propose a way to apply DNA computing to this human resource management problem, and to measure its effectiveness in rearranging employees to analyse the density of subgroups in a personnel network with valued relationships.
AB - One method for enhancing the quality of work life for companies or other organisations is to rearrange employees by detecting and analysing employees' close interpersonal relationships based on business implications. Although human resource managers can use various methods to enhance the quality of work life, one of the most widely used and effective methods is job rotation. In this paper, we select a model of a workplace where employees in a variety of job functions are sharing tasks, information, etc. through close interpersonal relationships, and we suppose a personnel network which contains strong terms of mutual understanding. However, with a huge number of employees it becomes extremely difficult to find the maximum clique of employees for rearrangement, meaning this is NP-hard. Therefore, we employ DNA computing, also known as molecular computation, to this rearranging problem. The goal of this paper is to propose a way to apply DNA computing to this human resource management problem, and to measure its effectiveness in rearranging employees to analyse the density of subgroups in a personnel network with valued relationships.
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M3 - Conference contribution
AN - SCOPUS:33750699358
SN - 3540465421
SN - 9783540465423
VL - 4253 LNAI - III
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 964
EP - 971
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
Y2 - 9 October 2006 through 11 October 2006
ER -