Decision support models and systems

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.

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

1. Introduction
2. Decision analysis
3. Decision support applications
4. Decision systems and decision support systems
5. Advanced decision modeling methods
6. Some Data-Driven Decision Support Methods
7. Practical training

• 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

Basic:

• Clemen RT. Making hard decisions: an introduction to decision analysis. Belmont, CA: Duxbury Press; 1996 Jan 1.
• Thakkar JJ. Multi-criteria decision making. Singapore: Springer; 2021 Feb 8.
• Ishizaka A, Nemery P. Multi-criteria decision analysis: methods and software. John Wiley & Sons; 2013 Jun 10. Catalogue

Additional:

• Bohanec, M. Odločanje in modeli. 1. ponatis. DMFA - založništvo, 2012. ISBN 978-961-212-190-7 Catalogue
• Bohanec M, Žnidaršič M, Rajkovič V, Bratko I, Zupan B. DEX methodology: three decades of qualitative multi-attribute modeling. Informatica. 2013;37(1). E-version
• 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
• Kochenderfer MJ, Wheeler TA, Wray KH. Algorithms for decision making. MIT press; 2022 Aug 16.
• Marchau VA, Walker WE, Bloemen PJ, Popper SW. Decision making under deep uncertainty: from theory to practice. Springer Nature; 2019. E-version
• Sharda R, Delen D, Turban E, Aronson J, Liang TP. Business intelligence and analytics: Systems for decision support. Pearson Higher Ed; 2014 Jan 14.
• Guerrero H, Guerrero R, Rauscher. Excel data analysis. Springer International Publishing; 2019.

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

Doc. dr. Adrian HERMES (formerly, Ahmad Hosseini) is an Assistant Professor at the School of Engineering and Management and the School of Viticulture and Enology at the University of Nova Gorica. He is also affiliated with the Center for Information Technologies and Applied Mathematics (CITAM). He is primarily interested in interdisciplinary research at the intersection of Industrial Engineering, Operations Research (OR), Computer Science, and Mathematical Optimization, focusing on theory, design, and implementation. Specifically, he is strongly inclined towards the modeling and applications of Industrial Optimization Problems.

Izbrane objave / Selected bibliography

1. HOSSEINI, Ahmad. Uncertainty-driven stability analysis of minimum spanning tree under multiple risk variations. Mathematics. Sep. 2025, vol. 13, issue 19, [article no.] 3100, 20 str., ilustr. ISSN 2227-7390. https://www.mdpi.com/2227-7390/13/19/3100, Repozitorij Univerze v Novi Gorici - RUNG, DOI: 10.3390/math13193100. [COBISS.SI-ID 251015171].

2. HOSSEINI, Ahmad. Max-type reliability in uncertain post-disaster networks through the lens of sensitivity and stability analysis. Expert systems with applications. [Online ed.]. May 2024, vol. 241, [article no.] 122486, str. 1-22, ilustr. ISSN 1873-6793. https://doi.org/10.1016/j.eswa.2023.122486, Repozitorij Univerze v Novi Gorici - RUNG, DOI: 10.1016/j.eswa.2023.122486. [COBISS.SI-ID 173538563]

3. HOSSEINI, Ahmad, WADBRO, Eddie, NGOC DO, Dung, LINDROOS, Ola. A scenario-based metaheuristic and optimization framework for cost-effective machine-trail network design in forestry. Computers and electronics in agriculture. [Print ed.]. Sep. 2023, vol. 212, [article no.] 108059, str. 1-13, ilustr. ISSN 0168-1699. Repozitorij Univerze v Novi Gorici - RUNG, DOI: 10.1016/j.compag.2023.108059. [COBISS.SI-ID 159537155].

4. ČESNIK, Urban, MARTELANC, Mitja, OVSTHUS, Ingunn, RADOVANOVIĆ VUKAJLOVIĆ, Tatjana, HOSSEINI, Ahmad, MOZETIČ VODOPIVEC, Branka, BUTINAR, Lorena. Functional characterization of Saccharomyces yeasts from cider produced in Hardanger. Fermentation. 2023, vol. 9, issue 9, [article no.] 824, str. 1-27. ISSN 2311-5637. https://www.mdpi.com/2311-5637/9/9/824, Repozitorij Univerze v Novi Gorici - RUNG, Digitalna knjižnica Univerze v Mariboru – DKUM, DOI: 10.3390/fermentation9090824, DOI: 20.500.12556/DKUM-86061. [COBISS.SI-ID 164729091].

5. HOSSEINI, Ahmad, WADBRO, Eddie. A hybrid greedy randomized heuristic for designing uncertain transport network layout. Expert systems with applications. [Print ed.]. Mar. 2022, vol. 190, [article no.] 116151, str. 1-10, ilustr. ISSN 0957-4174. Repozitorij Univerze v Novi Gorici - RUNG, DOI: 10.1016/j.eswa.2021.116151. [COBISS.SI-ID 141605891].