Design Optimization

  • Syllabus
  • Book
  • Schedule

Design Optimization Textbook

Edition 2 (2018)

  • Chapter 1: Introduction to Optimization-Based Design
  • Chapter 2: Modeling Concepts
  • Chapter 3: Unconstrained Optimization
  • Chapter 4: Derivatives
  • Chapter 5: Discrete Variable Optimization
  • Chapter 6: Genetic and Evolutionary Optimization
  • Chapter 7: Constrained Optimization 1: KKT Conditions
  • Chapter 8: Constrained Optimization 2: SQP, IP, and GRG
  • Chapter 9: Robust Design
  • References

Cite as: Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren, Second Edition, Brigham Young University, 2018.


Edition 1 (2013)

  • All Chapters: Optimization Methods for Engineering Design
  • Chapter 1: Optimization Design Basics
  • Chapter 2: Mathematical Modeling
  • Chapter 3: Unconstrained Optimization
  • Chapter 4: Discrete Optimization
  • Chapter 5: Genetic Algorithms
  • Chapter 6: Constrained Optimization, Part I
  • Chapter 7: Constrained Optimization, Part II
  • Chapter 8, Part 1: Robust Optimization
  • Chapter 8, Part 2: Interior Point Methods
  • Chapter 9: Dynamic Optimization (see additional course material)

Cite as: Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren, First Edition, Brigham Young University, 2013.

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Course Information

  • Overview
  • Syllabus
  • Schedule
  • Book Chapters 📒
  • Info Sheet
  • Expectations
  • Competencies
  • Optimization Software
  • YouTube Playlist

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

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

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  • 🎓 Engineering Computing
  • 🎓 Data Science
  • 🎓 Data-Driven Engineering
  • 🎓 Machine Learning
  • 🎓 Control (MATLAB)
  • 🎓 Control (Python)
  • 🎓 Optimization
  • 🎓 Dynamic Optimization

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Last modified October 02, 2018, at 01:54 PM