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論文中文名稱:TEAM FORMATION FOR MULTIPLE PROJECTS [以論文名稱查詢館藏系統]
論文英文名稱:TEAM FORMATION FOR MULTIPLE PROJECTS [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:管理學院
系所名稱:管理國際學生碩士專班 (IMBA)
畢業學年度:101
出版年度:102
中文姓名:Anne-SophieHuba
英文姓名:Hubault Anne-Sophie
研究生學號:100988013
學位類別:碩士
語文別:英文
口試日期:2013-06-11
論文頁數:49
指導教授中文名:吳建文
口試委員中文名:陳育威;杜壯
中文關鍵詞:Team FormationProject SchedulingData MiningFIM
英文關鍵詞:Team FormationProject SchedulingData MiningFIM
論文中文摘要:Realizing projects which are demanding in terms of resources and capabilities might need to be carried out by more than one person. Instead a set of individuals who will form a team can corporate to achieve these projects. Selecting the employees to form the best team and simultaneously choose which projects need to be realized is a tough decision problem frequently encountered in every enterprise.

This research considers the problem of such team formation for the realization of multiple projects. We consider some constraints such as the availability of the employees, the duration of the project and the profit of each project. The objective is to maximize the profit of the company by selecting the suitable time slots to form a team who can handle the project with the highest profit.

A mathematical model is provided for the problem. The feasible schedule will contain all the time slots that can be used to create teams. Those time slots have to meet the project constraints as well as the profit constraints. With this model, it will be possible to find out who will be selected to join the team. Also, to solve this model, an algorithm based on Frequent Itemset Mining (FIM) will be used. Experiments will then be performed to show the effectiveness and the performance of the model. This paper, team formation for multiple projects, bring new value by considering the employee’s unavailability and using FIM which was never done before in the literature.
論文英文摘要:Realizing projects which are demanding in terms of resources and capabilities might need to be carried out by more than one person. Instead a set of individuals who will form a team can corporate to achieve these projects. Selecting the employees to form the best team and simultaneously choose which projects need to be realized is a tough decision problem frequently encountered in every enterprise.

This research considers the problem of such team formation for the realization of multiple projects. We consider some constraints such as the availability of the employees, the duration of the project and the profit of each project. The objective is to maximize the profit of the company by selecting the suitable time slots to form a team who can handle the project with the highest profit.

A mathematical model is provided for the problem. The feasible schedule will contain all the time slots that can be used to create teams. Those time slots have to meet the project constraints as well as the profit constraints. With this model, it will be possible to find out who will be selected to join the team. Also, to solve this model, an algorithm based on Frequent Itemset Mining (FIM) will be used. Experiments will then be performed to show the effectiveness and the performance of the model. This paper, team formation for multiple projects, bring new value by considering the employee’s unavailability and using FIM which was never done before in the literature.
論文目次:Table of Contents

Abstract i
Acknowledgements ii
Table of Contents iii
List of Tables iv
List of Figures v
Chapter I: Introduction - 1
1.1 Study Purpose - 1
1.2 Research Procedure - 3
1.3 Study Structure - 4 -
Chapter II: Literature Review - 5
2.1 Project scheduling - 5
2.2 Team Formation - 14
Chapter III: Mathematical Model - 16
3.1 Problem Model - 16
3.2 Example - 19
Chapter IV: Algorithm Solution - 23
4.1 Frequent Itemset Mining - 23
4.1.1 Apriori Algorithm - 24
4.1.2 FPGrowth Algorithm - 27
4.1.3 Max-Miner Algorithm - 30
4.1.4 Mafia Algorithm - 32
4.2 Our Approach - 36
4.2.1 The Algorithm - 36
4.2.2 Example - 37
Chapter V: Experiments - 39
5.1 The procedure - 39
5.2 The results - 40
Chapter VI: Conclusion and Suggestions - 44
6.1 Conclusion - 44
6.2 Suggestions - 45
References - 47
論文參考文獻:References
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