Mathematical Programming

Course Information
TitleΜΑΘΗΜΑΤΙΚΟΣ ΠΡΟΓΡΑΜΜΑΤΙΣΜΟΣ / Mathematical Programming
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
Course ID40000519

Programme of Study: UPS of School of Mathematics (2014-today)

Registered students: 588
OrientationAttendance TypeSemesterYearECTS
CoreCompulsory Course215.5

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Instructors from Other Categories
Weekly Hours3
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
Required Courses
  • 0102 Introduction to Algebra
  • 0201 Calculus I
General Prerequisites
Elements of Linear Algebra Elementary Calculus
Learning Outcomes
Upon successful completion of the course students will: 1. have understood the importance of mathematical models in solving optimization problems. 2. Can model elementary linear and nonlinear (dynamic) problems. 3. Apply the Simplex method to solve linear problems. 4. Solve elementary dynamic programming problems such as: Elementary Transportation and Assignment problems, Tool Replacement, and Minimum-Cost Network Flow Problems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Design and manage projects
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Mathematical models. Linear programming. Graphical solution and graphical analysis of the sensitivity of the linear model. Simplex method. Introduction to Integer Programming. Transportation problem. Principles of dynamical programming. Non-linear methods of optimization. Applications.
Linear programming, Simplex method, Dynamical programming.
Educational Material Types
  • Notes
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Learning basic knowledge of the theory of mathematical programming. Learning how to model linear problems. Solving linear problems using the Simplex method. Solving problems using Dynamic Programming techniques. Practising to modelling by applying tools of mathematical programming.
Course Organization
Reading Assigment1234.1
Student Assessment
Written examination
Student Assessment methods
  • Written Exam with Extended Answer Questions (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Course Bibliography (Eudoxus)
- Εισαγωγή στην Επιχειρησιακή Ερευνα : Αλγόριθμοι & Εφαρμογές, Ν. Τσάντας, Π.-Χ. Γ. Βασιλείου, Ζήτη, 2000. - Γραμμικός Προγραμματισμός : Θεωρία και ασκήσεις, Σ. Κουνιάς, Δ. Φακίνος, Ζήτη, 1999.
Additional bibliography for study
- Linear Programming: J. P. Ignizio, T. M. Cavalier, Prentice Hall, 1994
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