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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    IE 510 | Course Introduction and Application Information

    Course Name
    Discrete Optimization
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    IE 510
    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 give the students an understanding and experience about discrete optimizaton problems, related concepts and exact and approximate solution techniques.
    Learning Outcomes

    The students who succeeded in this course;

    • Be able to develop a fundamental understanding of integer and combinatorial optimization problems
    • Be able to acquire modelling capabilities with binary and integer variables
    • Be able to use advanced modeling tools to formulate and solve complicated real-life optimization problems
    • Be able to analyze various optimization formulations in terms of their strength and learn ways to strengthen a weak formulation
    • Be able to apply various algorithms to solve integer and combinatorial optimization problems
    Course Description Formulation of integer and combinatorial optimization problems. Optimality conditions and relaxation. Polyhedral theory and integer polyhedra. Computational complexity. The theory of valid inequality, strong formulations. Duality and relaxation of integer programming problems. General and special purpose algorithms including branch and bound, decomposition, and cutting-plane algorithms.

     



    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
    2 Optimality, Relaxation and Bounds
    3 Optimality, Relaxation and Bounds
    4 Well-solved Cases: Network Flows, Shortest Path, Optimal Trees, Matching and Assignments
    5 Well-solved Cases: Network Flows, Shortest Path, Optimal Trees, Matching and Assignments
    6 Branch and Bound Methods
    7 Branch and Bound Methods
    8 Midterm exam
    9 Cutting Plane Algorithms: Valid Inequalities, Theory and Practice
    10 Cutting Plane Algorithms: Valid Inequalities, Theory and Practice
    11 Cutting Plane Algorithms: Valid Inequalities, Theory and Practice
    12 Dynamic Programming
    13 Approximation Algorithms
    14 Approximation Algorithms
    15 General Review and Evaluation
    16 General Review and Evaluation

     

    Course Notes/Textbooks Instructor notes and lecture slides
    Suggested Readings/Materials

    Integer Programming. Laurence A. Wolsey, Wiley, 1998. ISBN:  0471283665

    Integer and Combinatorial Optimization. Laurence A. Wolsey, George L. Nemhauser, Wiley, 1999. ISBN:  047182819X

     

    EVALUATION SYSTEM

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

    Weighting of Semester Activities on the Final Grade
    60
    Weighting of End-of-Semester Activities on the Final Grade
    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
    15
    4
    60
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    1
    60
    60
    Presentation / Jury
    0
    Project
    0
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    27
    27
    Final Exam
    1
    30
    30
        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.
    -
    -
    -
    -
    X
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    X
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.
    -
    -
    -
    -
    X
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    X
    -
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    X
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    -
    -
    X
    7 Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.
    -
    X
    -
    -
    -
    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.
    -
    -
    X
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    X
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    X
    -
    -
    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.
    -
    X
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    -
    X
    -
    -
    -

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

     

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