Decision Support and Risk Analysis

Recommended Prerequisites

Calculus, Linear Algebra, Probabilities and Statistics

Teaching Methods

Theoretical and methodological concepts are presented in tutorial lectures, being motivated by real-world problems and illustrated with application examples.
Software (commercial and public domain) packages are used to obtain solutions to the mathematical models, thus freeing the students for the more creative tasks of problem formulation, model building and critical analysis of results.

Learning Outcomes

Providing the students with methodological and application competences in the area of models and methods for decision support and risk analysis, in the context of engineering problems in which the existence of large volumes of data is a fundamental feature, enabling to identify types of problems, develop mathematical models that include the essential characteristics of those problems, apply algorithms to generate solutions for the models, and to perform a critical analysis of the solutions obtained.

Work Placement(s)

No

Syllabus

1. Decision analysis: Decisions without and with experimentation; Decision trees; Risk analysis
2. Multicriteria decision analysis: Choice, ranking and sorting problems; Notion of preferences; Outranking relations; Value functions
3. Multiobjective optimization: concepts of efficient/nondominated soltions; Scalarizing techniques; Interaactive methods; Preference learning
4. Efficiency analysis: Data Envelopment Analysis (DEA)

Head Lecturer(s)

Carlos Alberto Henggeler de Carvalho Antunes

Assessment Methods

Assessment
Mini Tests: 25.0%
Exam: 75.0%

Bibliography

- Henggeler Antunes, C., M. J. Alves, J. Clímaco. "Multiobjective Linear and Integer Programming", EURO Advanced Tutorials on Operational Research, Springer, 2016.
- Hillier, F. S., G. J. Lieberman. "Introduction to Operations Research", McGraw-Hill, 2015 (10th ed.).
- Cooper, W. W., L. Seiford, K. Tone. Data Envelopment Analysis - A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Springer, 2007