Course Information

Course Name	Turkish	Mühendislikte Optimizasyon Teknikleri
	English	Optimization Techniques in Engineering
Course Code	UUM 526E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Nazım Kemal Üre
Course Objectives		1- To give a detailed understanding of numerical optimization concepts and mathematical conditions for optimality 2- To understand and apply linear, non-linear, gradient-based, gradient-free, constrained and non-constrained optimization algorithms 3- To teach how to formulate a design problem as an optimization problem in the most efficient and correct way. 4- To teach how to choose the most convenient optimization algorithm for an optimization problem. 5- To give an understanding of how the results obtained by optimization procedure can be used towards a product
Course Description		Optimum Design Concepts, Lagrange Formulation, Karush-Kuhn Tucker necessary conditions, Linear Programming, Simplex method, Nonlinear Problems, Numerical Methods for Unconstrained Optimum Design, 1-D minimization, Steepest descent method, Conjugate gradient method, Newton’s method, Quasi Newton Methods, DFP method, BFGS method, Numerical Methods for Constrained Optimum Design, Sequential linear programming, Quadratic programming, Constrained steepest descent method, Constrained Quasi-Newton methods, Multi-objective Problems, Genetic Algorithms and Evolutionary Strategies, Multi-disciplinary Optimization and Sensitivity Analysis, Topology Optimization
Course Outcomes		M.Sc./Ph.D. students who successfully pass this course gain knowledge, skill and competency in the following subjects; 1- Understand numerical optimization concepts and mathematical conditions for optimality 2- Understand linear, non-linear, gradient-based, gradient-free, constrained and non-constrained optimization algorithms 3- Transform a design problem into an optimization problem and choose a feasible optimization algorithm 4- Carry an optimization project from the beginning to the end by himself/herself or as a team through programming or using a commercial software.
Pre-requisite(s)
Required Facilities
Other
Textbook		Chong, E. and Zak, S., 2001. An Introduction to Optimization, Wiley , NY.
Other References		Arora, J.S., 2004. Introduction to Optimum Design, Elsevier Academic Press, San Diego. Boyd, Stephen, and Lieven Vandenberghe. Convex optimization. Cambridge university press, 2004.

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