Design Optimization
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Course Information
Overview
Syllabus
Schedule
Book Chapters 📒
Info Sheet
Expectations
Competencies
Optimization Software
YouTube Playlist
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Homework
Optimization Basics
Optimize with Python
Tubular Column
Two Bar Truss
Step Cone Pulley
Beam Column
Crane Hook
Rocket Launch
Spring Design
Heat Integration
Slurry Pipeline
Oxygen Furance
Quasi-Newton Methods
Discrete Design
Simulated Annealing
KKT Conditions
Interior Point Method
Projects
Application Project
Solver Project
Activities
1-MATLAB and Python
2-Equation Residuals
3-Financial Objectives
4-Parallel Computing
5-Advanced Programming
6-Logical Conditions
7-Simulated Annealing
8-Climate Control
9-Dynamic Estimation
10-Vapor Liquid Equilibrium
11-Ethyl Acetate Kinetics
12-Dye Fading Kinetics
13-Linear Regression
14-Nonlinear Regression
15-Knapsack Optimization
16-Schedule Optimization
17-Global Optimization
18-Nonlinear Pricing
Lecture Notes
Optimization Introduction
Mathematical Modeling
Unconstrained Optimization
Discrete Optimization
Genetic Algorithms
Constrained Optimization
Robust Optimization
Dynamic Optimization
Extra Content
Box Folding
Circle Challenge
Linear Programming
Minimax or Maximin
Slack Variables
Related Courses
🎓 Begin Python
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🎓 Data Science
🎓 Data-Driven Engineering
🎓 Machine Learning
🎓 Control (MATLAB)
🎓 Control (Python)
🎓 Optimization
🎓 Dynamic Optimization
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