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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳政鴻(Cheng-Hung Wu) | |
| dc.contributor.author | Jan Leggen | en |
| dc.contributor.author | 揚磊 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:11:33Z | - |
| dc.date.available | 2021-11-03 | |
| dc.date.available | 2022-11-24T03:11:33Z | - |
| dc.date.copyright | 2021-11-03 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-26 | |
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(eds) Proceedings / Twentieth International Conference on Machine Learning: August 21 - 24, 2003, Washington, DC, USA, Menlo Park, Calif., AAAI Press. Chou, Y.-L., Lin, T.-Y., Wu, J.-Z. and Wu, C.-H. (2020) ‘An interactive method for multicriteria dispatching problems with unknown preference functions’, Computers Industrial Engineering, vol. 144, p. 106462 [Online]. DOI: 10.1016/j.cie.2020.106462. Cortes, C. and Vapnik, V. (1995) ‘Support-vector networks’, Machine Learning, vol. 20, no. 3, pp. 273–297 [Online]. DOI: 10.1007/BF00994018. Dembczyński, K., Kotłowski, W., Słowiński, R. and Szeląg, M. (2011) ‘Learning of Rule Ensembles for Multiple Attribute Ranking Problems’, in Fürnkranz, J. and Hüllermeier, E. (eds) Preference Learning, Berlin, Heidelberg, Springer Berlin Heidelberg, pp. 217–247. Fan, R.-E., Chang, K.-W., Hsieh, C.-J., Wang, X.-R. and Lin, C.-J. (2008) ‘LIBLINEAR: A library for large linear classification’, Journal of Machine Learning Research, no. 9, pp. 1871–1874. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80642 | - |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:11:33Z (GMT). No. of bitstreams: 1 U0001-2110202100263900.pdf: 5080151 bytes, checksum: bae880457398b95cf5dd2c99419cf782 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員會審定書 ...I Abstract ...II Contents ... III List of Figures ...V List of Tables ... VI Chapter 1 Introduction ... 1 1.1 Problem Background ... 2 1.2 Related Work ... 3 1.3 Research Objective ... 5 1.4 Research Contribution ... 6 1.5 Organization of the Thesis ... 8 Chapter 2 Background Knowledge ... 9 2.1 Interactive Centroid Method (ICM) ... 9 2.2 SVM Classification ... 12 2.3 Preference Learning ... 14 Chapter 3 Methodology ... 16 3.1 Assumptions and Limitations ... 16 3.2 Method Flow ... 17 3.3 Data Description ... 18 3.3.1 Training Data Extraction ... 19 3.3.2 Conversion to Pairwise Preference Relations ... 20 3.3.3 Training Data and Class Balancing ... 23 3.4 Learning and Prediction ... 24 3.4.1 SVC Training ... 24 3.4.2 SVC Ranking for new Demand Case ... 25 3.5 Final Interactive Comparison (Relaxed Points) ... 27 3.6 Illustrative Example ... 31 Chapter 4 Numerical Study and Sensitivity Analysis ... 42 4.1 Numerical Study Settings ... 42 4.2 Result Analysis ... 43 4.2.1 Raw Results without Final Interactive Comparison ... 43 4.2.1.1 Raw Results: Linear Preference Functions ... 44 4.2.1.2 Raw Results: Quadratic Preference Functions ... 46 4.2.2 Results with Final Interactive Comparison ... 47 4.2.2.1 Final Results: Linear Preference Functions ... 48 4.2.2.2 Final Results: Quadratic Preference Functions ... 49 4.3 Sensitivity Analysis ... 51 4.3.1 Impact of the Number of Training Demand Cases ... 51 4.3.2 Impact of Feature Scaling and Parameter Tuning ... 53 4.3.3 Impact of SVC Implementation ... 55 4.3.4 Impact of Release Rate for New Demand Cases ... 55 4.3.5 Impact of Movement Ratio in Final Interactive Comparison ... 57 Chapter 5 Conclusion and Future Research ... 60 Reference ... 62 Appendix A: Frontier LP Models ... 66 Appendix B: SVC Method Pseudo Code ... 67 Appendix C: Linear Preference Functions ... 72 Appendix D: Quadratic Preference Functions ... 75 | |
| dc.language.iso | en | |
| dc.subject | 偏好學習 | zh_TW |
| dc.subject | 多標準決策 | zh_TW |
| dc.subject | 未知的偏好函數 | zh_TW |
| dc.subject | 支援向量機 | zh_TW |
| dc.subject | Multi-criteria Decision-making | en |
| dc.subject | Preference Learning | en |
| dc.subject | Support Vector Machines | en |
| dc.subject | Unknown Preference Functions | en |
| dc.title | 決策者偏好學習與多目標排程最佳化 | zh_TW |
| dc.title | Preference Learning and Optimization for Multiple Objective Scheduling Problems | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 洪一薰(Hsin-Tsai Liu),陳文智(Chih-Yang Tseng),周育樂 | |
| dc.subject.keyword | 多標準決策,未知的偏好函數,支援向量機,偏好學習, | zh_TW |
| dc.subject.keyword | Multi-criteria Decision-making,Unknown Preference Functions,Support Vector Machines,Preference Learning, | en |
| dc.relation.page | 77 | |
| dc.identifier.doi | 10.6342/NTU202103950 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-10-26 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
| 顯示於系所單位： | 工業工程學研究所 | |
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