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Course Overview
This is a graduate level, mathematics-oriented and theoretical course. We will talk about mathematical definitions, properties, theorems, and a bit proofs. The readings assigned for the discussions will be academic and technical. Students are required to preview (預習) the assigned materials before specific dates (announced in the calendar in this Course Website.)
Course Format:
A combination of handouts delivering, Interactive classroom activities, blackboard writing, and slides/videos displaying.
Taking (some) classroom notes should be helpful.
Computer Techniques:
(1) AMPL: with the solvers on NEOS
(2) Other advanced computer languages and interfaces
Homework for Individuals :
(1) Preview of the specified texts announced on the course website
(2) Expected 3 homework sets
In-class discussions and in-class acitivites:
To enhance "effective learning", some in-class activities will be assigned to individuals or groups throughout the semester. Please maintain an open mind to participate.
Group Final Project (oral presentation) :
Assigned or selected project. Announced after midterm
Grading Weights:
Homework 20%;
In-class discussions and in-class presentations 20%;
Midterm Exam 30%;
Final Project Oral Presentation 30%
Academic Integrity and Student Responsibilities:
Cheating in any format is prohibited. Plagiarism is prohibited.
Topics and Homework Assignments Schedule:
Announced on this Course Website
Course Contents (new)
-Extension of the LP: more cases study
-Classical Nonlinear Proramming
-Modern Optimization for Machine Learning
Instructor - Prof. Yu-Ching Lee
I have been working in the area of optimization and operations research for almost 20 years.
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