Advanced Topics in Operation Research
Sustainable Development Goals
Learning Goals
This course aims to familiarize students with the procedures described in the program,it is also presented
the resolution for specific programs (free and open source) of all the problems described. In the second
part of the discipline, it presents an introduction to Graph Theory and Project Management (CPM) with
randomness in the duration of activity (Pert) and reducing the duration of the project with minimal cost
SKILLS:
The student should be able to a) specify theoretical models in the light of literature reviews, b) estimate,
validate and modify the models of interest, c) apply the knowledge acquired to real data and using the
appropriate software.
Contents
1. Optimization with Genetic Algorithms
2. Networks and Graphs
3. Dynamic programming
4. Project Management
5. Productivity and Efficiency Analysis
6. Markov Decision Processes
Teaching Methods
Lectures and practical classes supporting e-learning tools .
Introduction to theoretical concepts using examples of direct application in the field, aiming to show the
relevance of the syllabus.
Exercises directed, focusing on solving current problems and real, with the aim to develop a taste and
interest in the discipline and show its usefulness.
Focus on interpretation and analysis of data where possible using the "outputs" of the software used.
Students must complete the following self-employment:
Resolution of the proposed exercises in or with the software installed on computers at the University,
either with a calculator and tables.
Assessment
Students may choose between the regime of continuous assessment and by examination .
1. Continuous Assessment: Scheme frequency and presentation of short reports on subjects taught in the
class.
2. Scheme of examinations
Teaching Staff
- Vladimir Alekseevitch Bushenkov [responsible]
