113年第1學期-5569 Special Topics in Optimization 課程資訊

評分方式

評分項目	配分比例	說明
Participation	10	Student active participation in weekly meeting
Technical Ability	50	Student ability to follow technical optimization technique, both classical algorithm and modern tools
Written Report	25	Student ability to write academic report
Presentation and Discussion	15	Student ability to formally make oral presentation of academic work and engagement in the discussion

教育目標

1. In-depth discussion on classical optimization concepts and techniques, including linear programming, integer programming, non-linear programming, and multi-objective optimization. 2. Introduction of various tools to solve various forms of mathematical programming formulation, including Microsoft Excel Solver, LINGO, and Python Library. 3. Present state-of-the-art development in evolutionary technique for solving optimization problem, including Genetic Algorithm, Particle Swarm Optimization. 4. Discussion on application of various optimization techniques for solving problems in industrial engineering fields.

基本資料

選修課，學分數：3-0
上課時間：五/5,6,7[IEⅡ102]
修課班級：工工碩博1,2
修課年級：1年級以上
選課備註：英語授課

參考書目

1. Rao, Singiresu S. 2019. Engineering Optimization. (5th Edition). Wiley
2. Baker, Kenneth R. 2015. Optimization Modeling with Spreadsheets. (3rd Edition). Wiley
3. LINDO System. 2019. LINGO The Modeling Language and Optimizer.
4. Pereira, Valdecy. 2022. pyMetaheuristic: A Comprehensive Python Library for Optimization
5. Selected international journal articles in the area of Production/Operation Management