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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    M.SC. in Computer Engineering (With Thesis)

    IE 513 | Course Introduction and Application Information

    Course Name
    Mathematical Programming and Applications
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    IE 513
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives Purpose of this course is to provide an overview of basic linear programming and discuss advanced modeling and solution techniques.
    Learning Outcomes

    The students who succeeded in this course;

    • Be able to formulate engineering problems as mathematical programs
    • Be able to solve mathematical problems using appropriate methods
    • Be able to apply mathematical programming and solution methods to real life problems like network flow
    Course Description Topics of this course include theory, algorithms, and computational aspects of linear programming; formulation of problems as linear programs; duality and sensitivity analysis; primaldual simplex methods; the transportation, transshipment and assignment algorithms; extensions of linear programming; integer programming formulations and solution methods.

     



    Course Category

    		Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Introduction to linear programming Textbook Chapter 1
    2 Geometric solution Textbook Chapter 1
    3 Linear algebra, convex analysis and polyhedral sets Textbook Chapter 2
    4 Simplex method Textbook Chapter 3
    5 Simplex method Textbook Chapter 3
    6 Simplex method Textbook Chapter 3
    7 Starting solution and convergence Textbook Chapter 4
    8 Special simplex implementations and optimality conditions Textbook Chapter 5
    9 Midterm exam
    10 Duality Textbook Chapter 6
    11 Duality Textbook Chapter 6
    12 Sensitivitiy analysis Textbook Chapter 6
    13 Decomposition algorithms Textbook Chapter 7
    14 Integer Programming
    15 New Year
    16 Review of the Semester

     

    Course Notes/Textbooks

    Introduction to operations research. Hillier, F. S., & Lieberman, G. J., 10th edition, 2015, McGraw-Hill. 

     
    Suggested Readings/Materials

    Linear programming and network flows. Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D., 4th edition, 2011, John Wiley & Sons.
    Operations research: applications and algorithm. Winston, W. L., 4th edition, 2004, Thomson Learning.

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    20
    Presentation / Jury
    Project
    1
    15
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    25
    Final Exam
    1
    40
    Total

    Weighting of Semester Activities on the Final Grade
    3
    60
    Weighting of End-of-Semester Activities on the Final Grade
    1
    40
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    14
    6
    84
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    0
    Presentation / Jury
    0
    Project
    1
    33
    33
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    25
    25
    Final Exam
    1
    35
    35
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    		 PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering; evaluates, interprets and applies information.
    -
    -
    -
    -
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    -
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines.
    -
    -
    -
    -
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    -
    -
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    -
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs
    -
    -
    -
    -
    -
    7 Designs and implements studies based on theory, experiments and modelling; analyses and resolves the complex problems that arise in this process.
    -
    -
    -
    -
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
    -
    -
    -
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    -
    -
    -
    11 Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.
    -
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     

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