Operational Research IΙ
COURSE CONTENT
Section 1: Criteria for decision-making under uncertainty, Maximin, Maximax, Hurwicz, Minimax Regret, Mean value, Criteria for decision-making under risk, Maximization of expected return, Expected value of perfect information, Presenting computational (software) tools by realizing related exercises in Microsoft Excel
Section 2: Decision trees, Solving decision trees and risk-based problems, Use of probabilities, Bayes’ theorem, Presenting computational (software) tools by realizing related exercises in POM-QM for Windows.
Section 3: Utility/Value theory, Utility/Value functions, Linear & non-linear utility functions, Preference structures, Presenting computational (software) tools by realizing related exercises in Microsoft Excel
Section 4: Management of uncertainty, Sensitivity analysis, Risk analysis, Simulation-Monte Carlo technique, Presenting computational (software) tools by realizing related exercises in Microsoft Excel
Section 5: Multi-Criteria Decision Making, Introduction, Examples, Categories of MCDA methods, Typology of MCDA problems, Criteria, Pseudocriteria, Alternatives, Pareto optimal solutions.
Section 6: Criteria weights, Preference expression models, Intra-criteria & Inter-criteria preferences, Methods & techniques for weight estimation
Section 7: Multicriteria Utility/Value theory methods.
Section 8: PROMETHEE Methods, ELECTRE methods, Comparative application of multi-criteria methods, Presenting computational (software) tools by realizing related exercises using Microsoft Excel and Visual PROMETHEE.
Section 9: Queuing theory, Correlation between Exponential & Poisson distributions, Mathematical models & Queuing systems, Presenting computational (software) tools by realizing related exercises in POM-QM for Windows
Section 10: Network analysis, The Minimum Spanning Tree, Shortest Path and Maximum Flow problems
LEARNING OUTCOMES
The course aims to educate undergraduate students in specific fields of Operational Research having important applications in Engineering, Industry, Management and Decision Making. The purpose is to familiarize students with methods and techniques to deal with problems under uncertainty and risk, but also under a multiple criteria framework with various alternatives. In addition, the course addresses a group of basic techniques for estimating the weighting factors of criteria. Special sections are devoted to Utility Theory, Simulation and Queuing Theory.
Within this course, the students are expected to:
- Get familiarized with a significant number of quantitative methods, understand their usefulness and their appropriateness in decision-making support.
- Analyze complex and multiparametric systems considering technical, economic, environmental and social dimensions.
- Formulate and model a decision-making problem choosing the most appropriate method to handle it
- Understand and interpret the results of an applied methodology, take uncertainty into account and identify the problem’s crucial parameters
- Compare different methodologies and evaluate their advantages and disadvantages.
- Use modern computational (software) tools to develop and solve decision-making problems as well as analyze the solution obtained.
Course Features
- Lectures 0
- Quizzes 0
- Skill level All levels
- Language English
- Students 0
- Assessments Yes