040894 PR KFK PM/SCM/TL: Practical Course LP-Modeling I (2011S)
Continuous assessment of course work
Labels
please check the course'>http://prolog.univie.ac.at/teaching/LVAs/LP-PR/SS11/PartI/">course webpage for up-to-date information
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 07.02.2011 09:00 to Th 17.02.2011 17:00
- Registration is open from We 23.02.2011 09:00 to Fr 25.02.2011 14:00
- Deregistration possible until Mo 14.03.2011 23:59
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Thursday
03.03.
08:30 - 12:00
EDV-Labor 3
Thursday
10.03.
08:30 - 12:00
EDV-Labor 3
Thursday
17.03.
08:30 - 12:00
EDV-Labor 3
Thursday
24.03.
08:30 - 12:00
EDV-Labor 3
Thursday
31.03.
08:30 - 12:00
EDV-Labor 3
Thursday
07.04.
08:30 - 12:00
EDV-Labor 3
Thursday
14.04.
08:30 - 12:00
EDV-Labor 3
Friday
15.04.
08:00 - 12:00
EDV-Labor 3
Thursday
05.05.
08:30 - 12:00
EDV-Labor 3
Tuesday
28.06.
10:30 - 17:00
Hörsaal 13 Fakultätslounge
Information
Aims, contents and method of the course
Assessment and permitted materials
In order to pass the course you’ll need to complete the following tasks:* [30%] final exam - part I (theoretical stuff, written, individually, closed-book)
* [30%] final exam - part II (practical stuff, computer-based, individually, closed-book)
* [40%] homeworks (theoretical and practical in nature, Kreuzerlliste - for details see below)
o at least 50% of all assigned homeworks need to be prepared
o you will be picked randomly in order to present your homework at the beginning of class
o in case you fail to explain what you were supposed to prepare I'll consider this as an act of cheating ("Erschleichung von Teilleistungen")
o no hand-ins before or after class. no exceptions.
* in order to pass the course you need to
o prepare at least 50% of all assigned homework examples
o achieve at least 50% on both exams (cumulative)
* [30%] final exam - part II (practical stuff, computer-based, individually, closed-book)
* [40%] homeworks (theoretical and practical in nature, Kreuzerlliste - for details see below)
o at least 50% of all assigned homeworks need to be prepared
o you will be picked randomly in order to present your homework at the beginning of class
o in case you fail to explain what you were supposed to prepare I'll consider this as an act of cheating ("Erschleichung von Teilleistungen")
o no hand-ins before or after class. no exceptions.
* in order to pass the course you need to
o prepare at least 50% of all assigned homework examples
o achieve at least 50% on both exams (cumulative)
Minimum requirements and assessment criteria
The purpose of this course is to introduce students to mathematical programming which is extensively used in production and logistical management. In this course we will cover linear programming and prototype applications. Special emphasis will be given to linear programming modeling and its economic interpretation (duality theorem, complementary slackness, sensitivity analysis, etc.), and solving optimization methods using computers.
Students are expected to already know how to deal with Excel¿s optimization module to solve LP problems numerically, but later a state-of-the-art computer software, XPress-MP, will be introduced. Excel is fine for solving structurally simple and small scale problems, but for large scale and complex problems XPress is incomparable convenient. Therefore students are expected to be fluent in XPress by the end of this course.
Students are expected to already know how to deal with Excel¿s optimization module to solve LP problems numerically, but later a state-of-the-art computer software, XPress-MP, will be introduced. Excel is fine for solving structurally simple and small scale problems, but for large scale and complex problems XPress is incomparable convenient. Therefore students are expected to be fluent in XPress by the end of this course.
Examination topics
Students will learn how to develop linear models and implement them using XpressMP
Reading list
* Class Notes (electronic copies will be made available online)
* Applications of optimization with Xpress-MP, by Christelle Guéret, Christian Prins & Marc Sevaux
* An Introduction to Management Science (quantitative approaches to decision making), by Anderson and Sweeney
* Operations Research, by Hillier and Liebermann
* Applications of optimization with Xpress-MP, by Christelle Guéret, Christian Prins & Marc Sevaux
* An Introduction to Management Science (quantitative approaches to decision making), by Anderson and Sweeney
* Operations Research, by Hillier and Liebermann
Association in the course directory
Last modified: Mo 07.09.2020 15:29
* Introduction to XPress-MP
* Simplex Method (brief repetition)
* Sensitivity Analysis & its economic interpretation
* Advanced Modelling Techniques