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題名 Analyzing the Density of Subgroups in Valued Relationships Based on DNA Computing 作者 鄭至甫
Jeng, Jyh‐Fu貢獻者 科管智財所 日期 2006 上傳時間 7-Nov-2014 16:03:03 (UTC+8) 摘要 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. 關聯 Lecture Notes in Artificial Intelligence, 4253, 964-971 資料類型 article dc.contributor 科管智財所 en_US dc.creator (作者) 鄭至甫 zh_TW dc.creator (作者) Jeng, Jyh‐Fu en_US dc.date (日期) 2006 en_US dc.date.accessioned 7-Nov-2014 16:03:03 (UTC+8) - dc.date.available 7-Nov-2014 16:03:03 (UTC+8) - dc.date.issued (上傳時間) 7-Nov-2014 16:03:03 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/71243 - dc.description.abstract (摘要) 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. en_US dc.format.extent 119 bytes - dc.format.mimetype text/html - dc.language.iso en_US - dc.relation (關聯) Lecture Notes in Artificial Intelligence, 4253, 964-971 en_US dc.title (題名) Analyzing the Density of Subgroups in Valued Relationships Based on DNA Computing en_US dc.type (資料類型) article en
