Welcome to the GitHub repository containing lecture notes for VÉL113F Design and Optimization. These notes are meant to supplement face-to-face learning sessions and provide in-depth knowledge on the topics covered during the course.
This course dives into the world of optimum design concepts, emphasizing both linear and nonlinear programming. Students will explore both constrained and unconstrained optimum design problems. The course also introduces simulated annealing and genetic algorithms. Throughout the course, students will engage in projects that relate to real-world engineering design challenges.
By the end of this course, students will be able to:
- Basic Concepts: Use and explain the basic concepts of optimization.
- Simplex Method: Derive and explain the Simplex method for linear optimization.
- Nonlinear Optimization: Derive and explain classical nonlinear optimization methods for unconstrained problems.
- Constrained Nonlinear Optimization: Derive and explain the conjugate gradient method, first and second-order optimality conditions, and classical methods for constrained nonlinear optimization problems.
- Metaheuristics Methods: Develop and implement metaheuristics methods.
These notes and all associated materials are shared under the MIT license. Please refer to the LICENSE.md file for more details.
For questions or clarification on any topic, reach out to the course instructor via e-mail. You can also create an issue in this repository.