Dear students,
Please attend our onsite class on Monday, November 9, 2026. We will review both Linear Programming (LP) and Nonlinear Programming (NLP), work through calculations together, and address questions raised in your Exit Tickets and feedback.
Before class, please study the new 26-slide review with English narration. The narration takes approximately 14 minutes; allow additional time to pause and solve the practice questions.
Review slides with narration:
https://www.skhgroup.net/teaching/2105623/onsite-review-20261109/slides.html
Slide PDF:
https://www.skhgroup.net/teaching/2105623/onsite-review-20261109/Review-slides.pdf
PowerPoint with embedded narration:
https://www.skhgroup.net/teaching/2105623/onsite-review-20261109/Review-narrated.pptx
The review covers:
• LP: the meaning of primal and dual variables, construction of the dual, optimality certificates, and when shadow prices can be used.
• NLP: convexity, stationary points versus minima, gradient descent calculations, step-size limits, and checking Newton directions.
• A short KKT example showing why an active constraint can have a zero multiplier.
Please attempt the practice questions on slides 7 and 20 before viewing their solutions. Bring your calculations and specific questions to class, and bring a laptop if available for the Python examples. We will also clarify the main learning objectives and how to prepare for the examination.
Original LP materials and Python lab:
https://www.skhgroup.net/teaching/2105623/lp-duality/narrated/lab.html
Original NLP materials and Python lab:
https://www.skhgroup.net/teaching/2105623/nlp-session-1/
If you have not yet submitted the relevant Exit Tickets, please complete them after studying:
LP: https://optimization-2105623-class-check.soorathep-k.chatgpt.site/lp-duality
NLP: https://optimization-2105623-class-check.soorathep-k.chatgpt.site/nlp-session-1
Thank you. I look forward to working through your questions together in class.