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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/71243

Title:	Analyzing the Density of Subgroups in Valued Relationships Based on DNA Computing
Authors:	鄭至甫 Jeng, Jyh‐Fu
Contributors:	科管智財所
Date:	2006
Issue Date:	2014-11-07 16:03:03 (UTC+8)
Abstract:	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.
Relation:	Lecture Notes in Artificial Intelligence, 4253, 964-971
Data Type:	article
Appears in Collections:	[Graduate Institute of TIPM] Periodical Articles

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