Course Name Code Semester T+U Hours Credit ECTS
Optimization Techniques In Engineering EEM 505 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Compulsory
Course Coordinator Doç.Dr. GÖKÇEN ÇETİNEL
Course Lecturers Doç.Dr. GÖKÇEN ÇETİNEL, Doç.Dr. İRFAN YAZICI,
Course Assistants
Course Category Available Basic Education in the Field
Course Objective

To understand basic linear and nonlinear optimisation techniques
To formulize optimisation problems correctly
To apply optimisation techniques to the enginerring problems
To solve complicated engineering problems with learned optimisation techniques

Course Content

Week 1:  Introduction to Optimization: Statement of an Optimization Problem, Classification of Optimization Methods, Optimization Techniques.


Week 2: Background (Minimum and Maximum points of functions, convex and concave functions)


Week 3: Classical Optimization Techniques I: Single Variable Optimization, Multivariate Optimization with no Constraints.


Week 4: Classical Optimization Techniques II: Multivariate Optimization with Equality Constraints, Direct Substitution, Constrained Variation, Lagrange Multipliers.


Week 5: Classical Optimization Techniques III: Multivariate Optimization with Inequality Constraints, Kuhn-Tucker Conditions, Constraint Qualification, Convex Programming Problem.


Week 6: Linear Programming I: Applications of LP, Standard form of LP, Pivotal Reduction.


Week 7: Linear Programming II: Simplex Algorithm.


Week 8: Identifying an Optimal Point, İmproving a Non-optimal Basic Feasible Solution, Two Phases of Simplex Method.


Week 9: Nonlinear Programming I: One Dimensional Minimization Methods, Elimination Methods, Comparison of Methods.


Week 10: Nonlinear Programming II: Interpolation Methods, Direct Root Methods.


Week 11: Nonlinear Programming III: Unconstraint Optimization Techniques, Rate of Convergence, Scaling of Design Variables.


Week 12: Direct Search Methods


Week 13: Indirect Search Methods


Week 14: Final Projects. 

# Course Learning Outcomes Teaching Methods Assessment Methods
Week Course Topics Preliminary Preparation
Course Notes <p>Powerpoint presentations, lecture notes and books.&nbsp;</p>
Course Resources

1. Introduction to Optimization, P. Pedregal, Springer, 2003.
2. Numerical Optimization, J. Nocedal, S. J. Wright, Springer, 2nd Edition,2006.
3. Engineering Optimization Theory and Practice, S. S. Rao, Wiley, 4th Edition, 2009.

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Ability; to Access to wide and deep information with scientific researches in the field of Engineering, evaluate, interpret knowledge and implement. X
2 Ability; To complete and implement “Limited or incomplete data” by using the scientific methods. To stick knowledge of different disciplinarians together. X
3 Ability; to consolidate engineering problems, develop proper method to solve and apply innovative solutions. X
4 Ability; To develop new and original ideas and methods, To develop new innovative solutions at design of system, component or process
5 Comprehensive information on modern techniques, methods and their borders which are being applied to engineering. X
6 Ability; to design and apply analytical, modeling and experimental based research, analyze and interpret the faced complex issues during the design and apply process. X
7 High level ability to define the required information, data and reach, assess. X
8 Ability; To lead multi-disciplinary teams To take responsibility to define approaches for complex situations.
9 Systematic and clear verbal or written transfer of the process and results of studies at national and international environments
10 Social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation, announcement.
11 Awareness at new and developing application of profession and ability to analyze and study on those applications.
12 Ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment.
Evaluation System
Semester Studies Contribution Rate
1. Ödev 10
1. Performans Görevi (Seminer) 30
1. Ara Sınav 50
2. Ödev 10
Total 100
1. Yıl İçinin Başarıya 60
1. Final 40
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 2 2
Quiz 1 2 2
Assignment 2 10 20
Project / Design 1 20 20
Final examination 1 2 2
Total Workload 142
Total Workload / 25 (Hours) 5.68
dersAKTSKredisi 6