Required: "Diseño y simulación de sistemas productivos" (3rd year)

- Knowledge of general techniques to support industrial engineering decision making in multi-organizational and multi-decision agent context. - Identify situations where each technique apply. - Understand the importance of possible deviations between the case study and the model applied. - Being able to implement the techniques studied. - Understand the role of the R+D+I in business competitiveness and its relationship to engineering, technological capital and entrepreneurship.

1. Introduction to decision analysis. Quantitative models for decision-making in industrial engineering. 2. Decision tree analysis. Expected Monetary Value. 3. Search and use of additional information. 4. Certainty Monetary Equivalent. Utility functions. 5. Application of utility functions to decision tree analysis. 6. Introduction to analytical utility functions. 7. Attitudes towards risk. Types of analytical utility functions. 8. Constant proportionality risk aversion analytical utility functions. 9. Game theory. Introduction. 10. Two-person zero-sum games. 11. Two-person non-zero-sum games. 12. Introduction to multicriteria decision making. 13. Goal Programming. Problem formulation and resolution. 14. Environmental applicacions of MCDM techniques. 15. ELECTRE method. Problem formulation and resolution. 16. Application to HHRR selection problems. 17. Research, development and innovation. Technological capital and competitiveness.

Lectures, exercises, practical sessions, cases and assignments to be carried out by the students and discussed during the sessions, readings assigned by the instructor or identified by the students.