Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 342134 Network Reliability 1 3.0 3 ★ Ping-Chen Chang GIEM 21 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	342134	Network Reliability	1	3.0	3	★	Ping-Chen Chang	GIEM	21	0

Course Plan：

Instructor Ping-Chen Chang　Office Hours

Email pcchang@ntut.edu.tw

Last Updated 2024-12-16 18:24:37

Course Objective 本課程著重於隨機流量網路(stochastic flow network)的可靠度評估、分析和決策。在整個課程中，我們將介紹與隨機流量網路相關的數值分析方法、模擬技術和最佳化問題。此外，我們將在隨機流量網路模型的框架內深入探討最快路徑、多商品、路由政策和負載管理問題等主題。學生將有機會將這些方法和模型應用到實際系統中，包括電腦網路、電信、城市交通系統、電力傳輸網路和製造系統。 This course emphasizes the reliability evaluation, analysis, and decision-making aspects of stochastic flow networks. Throughout the course, we will introduce analytical methodologies, simulation techniques, and optimization problems related to stochastic flow networks. Furthermore, we will delve into topics like quickest path, multi-commodity, routing policies, and load management issues within the framework of stochastic flow network models. Students will have the opportunity to apply these methodologies and models to practical systems, including computer networks, telecommunications, urban traffic systems, power transmission networks, and manufacturing systems.

Course Schedule Week 1: Introduction Week 2: The basic concept of network reliability Week 3: MP-based reliability evaluation Week 4: MC-based reliability evaluation Week 5: QP-based reliability evaluation Weeks 6-7: Simulation in network reliability Weeks 8-9: Paper presentation for relevant works Week 10: Maintainable network – Estimate and exact solutions Weeks 11-13: Manufacturing network Week 14: Stochastic project network Week 15: Optimization/AI issues in network reliability Weeks 16-18: Final presentation

Evaluation and grading policy Class Participation 30% Paper Presentation 30% Final Presentation 40%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
Materials from SCI journal papers.

The access to curricular consultation 18th week: In-class discussion if needed
Students may contact me by Email.
Office hour: Mon. 10:00 - 12:00; Wed. 13:00 - 17:00

The course corresponds to the SDGs SDG12：負責任的消費與生產（Responsible Consumption and Production）

Does the course incorporate AI

Note
　

Instructor	Ping-Chen Chang　Office Hours
Email	pcchang@ntut.edu.tw
Last Updated	2024-12-16 18:24:37
Course Objective	本課程著重於隨機流量網路(stochastic flow network)的可靠度評估、分析和決策。在整個課程中，我們將介紹與隨機流量網路相關的數值分析方法、模擬技術和最佳化問題。此外，我們將在隨機流量網路模型的框架內深入探討最快路徑、多商品、路由政策和負載管理問題等主題。學生將有機會將這些方法和模型應用到實際系統中，包括電腦網路、電信、城市交通系統、電力傳輸網路和製造系統。 This course emphasizes the reliability evaluation, analysis, and decision-making aspects of stochastic flow networks. Throughout the course, we will introduce analytical methodologies, simulation techniques, and optimization problems related to stochastic flow networks. Furthermore, we will delve into topics like quickest path, multi-commodity, routing policies, and load management issues within the framework of stochastic flow network models. Students will have the opportunity to apply these methodologies and models to practical systems, including computer networks, telecommunications, urban traffic systems, power transmission networks, and manufacturing systems.
Course Schedule	Week 1: Introduction Week 2: The basic concept of network reliability Week 3: MP-based reliability evaluation Week 4: MC-based reliability evaluation Week 5: QP-based reliability evaluation Weeks 6-7: Simulation in network reliability Weeks 8-9: Paper presentation for relevant works Week 10: Maintainable network – Estimate and exact solutions Weeks 11-13: Manufacturing network Week 14: Stochastic project network Week 15: Optimization/AI issues in network reliability Weeks 16-18: Final presentation
Evaluation and grading policy	Class Participation 30% Paper Presentation 30% Final Presentation 40%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No Materials from SCI journal papers.
The access to curricular consultation	18th week: In-class discussion if needed Students may contact me by Email. Office hour: Mon. 10:00 - 12:00; Wed. 13:00 - 17:00
The course corresponds to the SDGs	SDG12：負責任的消費與生產（Responsible Consumption and Production）
Does the course incorporate AI
Note