An introduction to deterministic
optimization methodologies with the emphasis on linear
optimization; discrete and non-linear optimization including
algorithms and computations. Applications will be introduced as
appropriate in seminars.
Contents:
1. Introduction to Operations Research, System Modeling Principles.
2. Model Building in Linear Programming Models
3. Applications and Special Types of Mathematical Programming Model.
4. Graphical Solution of Linear Programming Model.
5. The Simplex Method.
6. Duality in Linear Optimization.
7. Sensitivity Analysis.
8. The Transportation Problem.
9. General Methods for Integer Programming.
10. Dynamic Optimization.
11. Non-linear Optimization.
12. System Approach to Problem Solving. Identification of Systems.
13. System Design of Socio-economic Systems.
Recommended literature:
Recommended literature:
1. Hillier, F.S., Lieberman, G.J.: Introduction to Operations Research. McGraw-Hill 2015
2. Taha, A.H.: Operations Research - An Introduction. Prentice Hall 2011
3. Newton, S.C, Sarker, A.R.: Optimization Modelling. A Practical Approach. CRC Press 2007
Keywords:
Optimization, Linear Programming, Simplex Method, Systems
Abbreviations used:
Semester:
W ... winter semester (usually October - February)
S ... spring semester (usually March - June)
W,S ... both semesters
Mode of completion of the course:
A ... Assessment (no grade is given to this course but credits are awarded. You will receive only P (Passed) of F (Failed) and number of credits)
GA ... Graded Assessment (a grade is awarded for this course)
EX ... Examination
A, EX ... Examination (the award of Assessment is a precondition for taking the Examination in the given subject)