|Course Name||Code||Semester||T+U Hours||Credit||ECTS|
|Optimization Techniques In Engineering||EEM 505||0||3 + 0||3||6|
|Recommended Optional Courses|
|Course Coordinator||Doç.Dr. GÖKÇEN ÇETİNEL|
|Course Lecturers||Doç.Dr. GÖKÇEN ÇETİNEL, Doç.Dr. İRFAN YAZICI,|
|Course Category||Available Basic Education in the Field|
To understand basic linear and nonlinear optimisation techniques
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. </p>|
1. Introduction to Optimization, P. Pedregal, Springer, 2003.
|Order||Program Outcomes||Level of Contribution|
|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.|
|Semester Studies||Contribution Rate|
|1. Performans Görevi (Seminer)||30|
|1. Ara Sınav||50|
|1. Yıl İçinin Başarıya||60|
|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|
|Project / Design||1||20||20|
|Total Workload / 25 (Hours)||5.68|