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WB1440: Eng. Optimization: Concept & Applications
ECTS: 3
Responsible Instructor: Dr.ir. M. Langelaar
Instructor: Prof.dr.ir. A. van Keulen
Contact Hours / Week x/x/x/x: 0/0/4/0
Education Period: 3
Start Education: 3
Exam Period: Different, to be announced
Course Language: English
Required for: wb1441
Expected prior knowledge: Basic knowledge of mechanical engineering and mathematics. Experience with Matlab is helpful.
Course Contents: Formulation of optimization problems
Typical characteristics of optimization problems
Minimization without constraints
Constrained minimization
Simple optimization algorithms
Discrete design variables
Approximation concepts
Sensitivity analysis
Study Goals: The student is able to formulate a proper optimization problem in order to solve a given design problem, and is able to select a suitable approach for solving this problem numerically. Furthermore, he is able to interpret results of completed optimization procedures.
More specifically, the student must be able to:
1. formulate an optimization model for various design problems
2. identify optimization model properties such as monotonicity, (non-)convexity and (non-) linearity
3. identify optimization problem properties such as constraint dominance, constraint activity, well boundedness and convexity
4. apply Monotonicity Analysis to optimization problems using the First Monotonicity Principle
5. perform the conversion of constrained problems into unconstrained problems using penalty or barrier methods
6. compute and interpret the Karush-Kuhn-Tucker optimality conditions for constrained optimization problems
7. describe the complications associated with the use of computational models in optimization
8. illustrate the use of compact modeling and response surface techniques for dealing with computationally expensive and noisy optimization models
9. perform design sensitivity analysis using variational, discrete, semi-analytical and finite difference methods
10. identify a suitable optimization algorithm given a certain optimization problem
11. perform design optimization using the optimization routines implemented in the Matlab Optimization Toolbox
12. derive a linearized approximate problem for a given constrained optimization problem, and solve the original problem using a sequence of linear approximations
13. describe the basic concepts used in structural topology optimization
Education Method: Lectures (2x2 hours per week), exercises
Computer Use: MATLAB is used for exercises and final project.
Literature and Study Materials: Course material: P.Y. Papalambros et al. Principles of Optimal Design: Modelling and Computation.
References from literature: R.T. Haftka and Z. Gürdal: Elements of Structural Optimization.
Assessment: MATLAB exercises, optimization project.
Percentage of Design: 80%
Design Content: The course is focusing on design optimization.
Last modified: 6 November 2013, 15:25 UTC
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