GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
LINEAR OPTIMIZATION/5071307
Course Title: LINEAR OPTIMIZATION
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
He /she knows application areas of optimization
He/she knows the generic structures of general problems linar programming
He /she knows how to develop solutions methods of linear optimization and its algorithmic property
He/she knows the specific importance of the simplex algorithm and its place in linear optimization
He/she knows the meaning and applications of primal and dual models and algorithms in linear optimization
He / she knows about the Kuhn-Tucker optimality conditions in linear optimization
He/she knows about the decomposition methods for large scale linear structures.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Optimization: Linear optimization, mathematical basis, modeling and examples.
2. Week  Vector space, matrices, system of simultaneous linear equations.
3. Week  Convex sets and convex functions, polyhedral sets.
4. Week  Simplex method: extreme points and optimality, basdic feasible soltions.
5. Week  Simplex method: a key to simplex method, geometric motivation, and its algebra.
6. Week  Starting solution and termination: basic feasible solutions.
7. Week  Starting solution and termination: artificial starting solutions.
8. Week  Starting solution and termination: special cases.
9. Week  Midterm I.
10. Week  Special simplex implementations.
11. Week  Optimality condition on linear programming
12. Week  Duality: formulations and primal-dual relationships.
13. Week  Post-optimality analysis: dual-simplex method
14. Week  Post-optimality analysis: parametrical analysis.
15. Week  Decomposition principle.
16. Week  Final exam
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
1
20
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
15
3
45
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
10
1
10
 Searching in Internet and Library
3
3
9
 Material Design and Implementation
5
1
5
 Report Preparing
2
6
12
 Preparing a Presentation
1
3
3
 Presentation
2
6
12
 Midterm Exam and Preperation for Midterm Exam
2
6
12
 Final Exam and Preperation for Final Exam
1
2
2
 Other (should be emphasized)
5
15
75
 TOTAL WORKLOAD: 
185
 TOTAL WORKLOAD / 25: 
7.4
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Can Reach the information in width and in depth by conducting scientific research in the field, evaluate, interpret and apply the information.X
2Has comprehensive knowledge about current techniques and methods applied in engineering and their limitations.X
3Completes and applies knowledge using scientific methods, using uncertain, limited or incomplete data; use information from different disciplines together.X
4Aware of the new and emerging practices of the profession, examines and learns when needed.X
5Defines and formulates problems related to the field, develops methods to solve them and applies innovative methods in solutions.X
6Develops new and / or original ideas and methods; design complex systems or processes and develop innovative / alternative solutions in their designs.X
7Designs and applies theoretical, experimental and modeling based research; examines and solves the complex problems encountered in this process.X
8Can work effectively in disciplinary and multidisciplinary teams, can lead such teams and develop solutions in complex situations; work independently and take responsibility.X
9Communicate verbally and in writing by using a foreign language at least at the B2 level of European Language Portfolio.
10Transfer the process and results of his / her studies in written and verbal form in a systematic and clear manner in national and international environments within or outside the field.X
11Knows the social, environmental, health, security, legal aspects of engineering applications as well as project management and business practices and is aware of the constraints that these impose on engineering applications.X
12It considers social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities.X
 -- NAME OF LECTURER(S)
   (Assoc.Prof. Mehmet ATAK and other relevant faculty members)
 -- WEB SITE(S) OF LECTURER(S)
   (www.gazi.edu.tr/~matak)
 -- EMAIL(S) OF LECTURER(S)
   (matak@gazi.edu.tr)