Decision Support Systems
General
Code: ΕΠ40
Language: Greek
Delivery: Face-to-face
Prerequisites:
Programming
Python
Workload
- Lectures: 39.0 hours
- Lab: 13.0 hours
- Study: 38.0 hours
- Project: 35.0 hours
Course Content
Decision Support Systems and Business Research - Types of Decision Making Problems - Decision Parameters - Decision Support - Decision Problem Categorization - Decision Making Process Phases - Decision Making System Components - Decision Making - Decisions - Architecture Decision- Methods of multi-criteria utility theory- Methods of superiority- Methods of multi-objective decision making or goal programming- Methods of analysis of preferences- Methods of raw set theory - Uncertainty in Decision Support Systems - Decision Trees - Intelligent Methods of DSS- Decision Making and Case studies -Simulation of Decision Support Systems
Learning Outcomes
The main goal of the course is the undergraduate students to get acquainted with the decision-making systems both in theory and in practice. This course will provide a first overview of decision-making systems and methodologies as well as familiarize students with the basic decision-making simulation tools. An important goal of this course is the students to gain in-depth knowledge as well as skills that will make it easier for them to engage with decision-making systems at a professional level, emphasizing the needs of the market. For this reason, in addition to the theoretical lectures, students will be given the opportunity to solve practical exercises and laboratory simulations.
Skills
- Independent Work
- Teamwork
- Adaptation to new situations
- Decision Making - Designing Decision Making Simulation Models - Experimenting with Decision Making Systems Simulation Models
- Promoting free, creative and inductive thinking