Information Package

Master's of Industrial Engineering with Thesis

END501

CONVEX ANALYSIS

Course Code
END501
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Explain the elements of linear algebra and multivariate calculus
  2. Solve systems of equations
  3. Define the convex analysis and its applications to optimisation of multivariate functions
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionSpecial topics in differential and integral calculations. Vector spaces. Matrices and determinants. Analytical and numerical methods for solving equation systems. Quadratic forms. Convex combination and convex sets. Convex and concave functions. Local and global optima in multi variate functions.
Course Contents
WEEK TOPICS
1st Week Linear Algebra and Real Analysis
2nd Week The linear space - Vectors and Matrices - Systems of Equations - Quadratic Forms
3rd Week Convex Sets and Functions - Convex and Affine Hulls
4th Week Relative Interior, Closure, and Continuity - Recession Cones
5th Week Convexity and Optimization -- Global and Local Minima
6th Week The Projection Theorem - The separation Theorem, Saddle Point and Minimax Theory
7th Week Subgradients and Constrained Optimization -- Directional Derivatives
8th Week Midterm
9th Week Subgradients and Subdifferentials -- Directional Derivative of the Max Function
10th Week Optimality Conditions
11th Week Introduction to Lagrange Multipliers
12th Week Informative Lagrange Multipliers - Sensitivity -- Alternative Lagrange Multipliers
13th Week Lagrangian Duality
14th Week Conjugate Duality
Recommended or Required ReadingDimitri P. Bertsekas (2003), Convex Analysis and Optimization, Athena Scientific (ISBN-10: 1886529450); (2) Stephen Boyd and Lieven Vandenberghe (2004), Convex Optimization, Cambridge University Press (ISBN-10: 0521833787).
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Practice
  • Presentation
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Project 1 30
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz
Individual or group work 14 14 196
Preparation for Final exam 1 25 25
Course hours 14 3 42
Preparation for Midterm exam 1 25 25
Laboratory (including preparation)
Final exam 1 2 2
Homework 1 14 14
Total Work Load306
Total Work Load / 30 (h)10.2
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3
K1 X X X
K2 X X
K3
K4
K5
K6
K7 X X X
K8
K9
K10
K11