School of Engineering and Management

Decision support models and systems

This course is part of the programme:
Master in Engineering and Management (Second Level)

Objectives and competences

The aim of this course is to learn advanced methods, techniques and systems for supporting complex real-life decision-making tasks. Special emphasis is on learning and mastering methods of decision analysis and multi-attribute modeling, practical use of decision-support software, and solving complex real-life decision problems.

Prerequisites

Undergraduate-level knowledge of mathematics, computer science and informatics.

Content (Syllabus outline)

1. Introduction

2. Decision analysis

3. Decision support applications

4. Decision systems and decision support systems

5. Advanced decision modeling methods

6. Practical training

Intended learning outcomes

  • Understanding the concepts of decision making, decision processes and decision support systems
  • Understanding the approaches of decision analysis and decision modeling
  • Obtaining the ability to identify decision problems and specify its properties and components
  • Learning how to develop and apply a decision model in real-life decision problems
  • Acquiring basic skills for using decision support and decision modeling software

Readings

    • M. Bohanec: Odločanje in modeli. 1. ponatis. DMFA – založništvo, 2012. ISBN 978-961-212-190-7
    • S. Greco, M. Ehrgott, J.R. Figueira (ur.): Multiple Criteria Decision Analysis: State of the Art Surveys, International Series in Operations Research and Management Science, Volume 233. Springer 2016. ISBN 978-1-4939-3093-7
    • A. Ishizaka, P. Nemery, P: Multi-Criteria Decision Analysis: Methods and Software. Wiley 2013. ISBN 978-1119974079

Assessment

  • seminar work with oral defense • written or oral exam 50/50

Lecturer's references

Prof. Dr. Marko Bohanec is a senior researcher at the Jožef Stefan Institute, Department of Knowledge Technologies, Ljubljana, Slovenia, and professor of computer science at the University of Nova Gorica, Slovenia. His major research interests are related to decision support systems and data mining, and in particular to qualitative hierarchical modeling and machine learning. He has extensive experience in decision-making consulting, developing decision-support software, and collaborating in EU research projects.

Selected bibliography

BOHANEC, Marko. Odločanje in modeli, (Učbeniki in priročniki). 1. ponatis. Ljubljana: DMFA – založništvo, 2012. XV, 313 str.. ISBN 978-961-212-190-7. [COBISS.SI-ID 260642816]

BOHANEC, Marko, ŽNIDARŠIČ, Martin, RAJKOVIČ, Vladislav, BRATKO, Ivan, ZUPAN, Blaž. DEX methodology: Three decades of qualitative multi-attribute modeling. Informatica (Ljublj.), 2013, vol. 37, no. 1, str. 49-54. [COBISS.SI-ID 26664999]

BOHANEC, Marko, MILEVA BOSHKOSKA, Biljana, PRINS, Theo W., KOK, Esther. SIGMO: A decision support system for identification of genetically modified food or feed products. Food control, ISSN 0956-7135. [Print ed.], 2016, vol. 71, str. 168-177. [COBISS.SI-ID 29620007]

BOHANEC, Marko, TRDIN, Nejc, KONTIĆ, Branko. A qualitative multi-criteria modelling approach to the assessment of electric energy production technologies in Slovenia. Central European Journal of Operations Research, ISSN 1435-246X, 2017, vol. 25, no. 3, str. 611-625. [COBISS.SI-ID 29867815]

TRDIN, Nejc, BOHANEC, Marko. Extending the multi-criteria decision making method DEX with numeric attributes, value distributions and relational models. Central European Journal of Operations Research, ISSN 1435-246X, 2018, vol. 26, no. 1, str. 1-41. [COBISS.SI-ID 30210087]

BOHANEC, Marko, MILJKOVIĆ, Dragana, VALMARSKA, Anita, MILEVA BOSHKOSKA, Biljana, et al. A decision support system for Parkinson disease management: Expert models for suggesting medication change. V: DSS research delivering high imacts to business and society, (Journal of decision systems, ISSN 1246-0125, vol. 27, no. S1, 2018). London: Taylor & Francis. 2018, vol. 27, sup. 1, str. 164-172. [COBISS.SI-ID 31392551]

University course code: 2GI011

Year of study: 1

Course principal:

Lecturer:

ECTS: 9

Workload:

  • Lectures: 30 hours
  • Exercises: 15 hours
  • Individual work: 180 hours

Course type: elective

Languages: slovene

Learning and teaching methods:
• lectures, where the contents of the syllabus will be presented and explained. • hands-on exercises, where the students will use the concepts from the lectures in practical problems and decision modeling programs. • individual work where the students will solve a practical assignment.