SDU Education Information System
   Home   |  Login Türkçe  | English   
 
   
 
 


 
Course Information
Course Unit Title : Computer Aided Optimization Techniques
Course Unit Code : 01MAE5111
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : 1
Semester : 1.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) :
Course Assistants :
Learning Outcomes of The Course Unit : 1) To gain optimization ability
2) To gain mathematical analysis ability
3) To apply optimization techniques to engineering problems
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Basic concepts, single and multi-dimensional, unconstrained and constrained problems, parameter optimization and mini-max theory, function optimization and calculus of variations, linear programming and simplex method, nonlinear programming and search techniques, software about optimization
Languages of Instruction : Turkish
Course Goals : 1) To give information about optimization.
2) To give information about mathematical analysis.
3) To teach about application of optimization techniques to engineering problems
Course Aims : To comprehend optimization techniques, to gain mathematically formulating and solving ability of optimization problems, to analysis different engineering problems with application of optimization models
WorkPlacement   Not Available
Recommended or Required Reading
Textbook : S. C. Chapra, R. P. Canale, Mühendisler için sayısal yöntemler, Literatür yayınları, No:82
Additional Resources : PIERRE, D. A., Optimization Theory With Applications, Wiley, 1969.
REKLAITIS, G. V., RAVINDRAN, A., RAGSDELL, K. M., Engineering Optimization: Methods and Applications, Wiley, 1983.
Material Sharing
Documents :
Assignments :
Exams :
Additional Material :
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 3 42  
Homeworks :
3 10 30  
Presentation :
4 10 40  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 10 10  
Finals :
1 10 10  
Workload Hour (30) :
30  
Total Work Charge / Hour :
174  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 100
Quiz :
0 0
Homework :
0 0
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Basic concepts, introduction to optimization
  Study Materials: Getting the course syllabus
2 One-Dimensional Unconstrained Optimization
  Study Materials: Research and reading
3 Golden division search
  Study Materials: Research and reading
4 Second degree interpolation
  Study Materials: Research and reading
5 Newton method
  Study Materials: Research and reading
6 Multidimensional Unconstrained Optimization
  Study Materials: Research and reading
7 Direct methods
  Study Materials: Research and reading
8 Gradient methods
  Study Materials: Research and reading
9 Constrained Optimization
  Study Materials: Research and reading
10 Linear programming
  Study Materials: Research and reading
11 Nonlinear programming
  Study Materials: Research and reading
12 Optimization with software packages
  Study Materials: Research and reading
13 Engineering applications
  Study Materials: Research and reading
14 Engineering applications
  Study Materials: Research and reading