GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
DISCRETE OPTIMIZATION/5081307
Course Title: DISCRETE 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
An ability to apply knowledge of mathematics, science, and engineering
An ability to identify, formulate, and solve engineering problems
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face.
 --WEEKLY SCHEDULE
1. Week  Repetition of continuous optimization
2. Week  Repetition of continuous optimization
3. Week  Definition of integer optimization, pure integer, mixed integer.
4. Week  Branch-bound technique, graphical solution.
5. Week  Branch-bound technique, table solution.
6. Week  Cutting methods, fractional cutting method -Penalty method.
7. Week  Cutting methods, fractional cutting method
8. Week  Cutting methods, dual cutting method
9. Week  Cutting methods, cutting method of mixed
10. Week  Cutting methods, primal cutting method
11. Week  Midterm Exam
12. Week  Definition of the logical 0-1 variables. Examples
13. Week  0-1 modeling. Examples
14. Week  Mixed modeling. Examples
15. Week  0-1 Optimization Algorithm
16. Week  Traveling salesman problems, the Hungarian method, their mathematical models, the optimal solution to TSP
 -- 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
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
0
 Searching in Internet and Library
5
10
50
 Material Design and Implementation
0
 Report Preparing
4
10
40
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
20
20
 Final Exam and Preperation for Final Exam
1
30
30
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
182
 TOTAL WORKLOAD / 25: 
7.28
 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.
3Completes and applies knowledge using scientific methods, using uncertain, limited or incomplete data; use information from different disciplines together.
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.
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.
 -- NAME OF LECTURER(S)
   (Prof. Cevriye GENCER and other relevant faculty members)
 -- WEB SITE(S) OF LECTURER(S)
   (https://websitem.gazi.edu.tr/site/ctemel)
 -- EMAIL(S) OF LECTURER(S)
   (ctemel@gazi.edu.tr)