Učni načrt predmeta

Predmet:
Podpora pri odločanju
Course:
Decision Support
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Informacijske in komunikacijske Tehnologije znanja 1 1
Information and Communication Knowledge Technologies 1 1
Vrsta predmeta / Course type
Izbirni
Univerzitetna koda predmeta / University course code:
IKT3-718
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
15 15 15 105 5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Marko Bohanec
Sodelavci / Lecturers:
prof. dr. Bojan Cestnik
Jeziki / Languages:
Predavanja / Lectures:
slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študij druge stopnje s področja informacijskih ali komunikacijskih tehnologij ali zaključen študij druge stopnje na drugih področjih z znanjem osnov s področja predmeta. Potrebna so tudi osnovna znanja matematike, računalništva in informatike.

Completed second cycle studies in information or communication technologies or completed second cycle studies in other fields with knowledge of fundamentals in the field of this course. Basic knowledge of mathematics, computer science and informatics is also requested.

Vsebina:
Content (Syllabus outline):

Uvod: odločanje in podpora pri odločanju, odločitveni proces, komponente odločanja, vrste odločanja, discipline, ki se ukvarjajo z odločanjem.

Odločitvena analiza: metode in tehnike modeliranja v odločitveni analizi, odločanje v pogojih negotovosti in s tveganjem, odločitvene tabele, odločitvena drevesa, diagrami vpliva, večkriterijski modeli, izbrane metode večkriterijskega modeliranja; Kepner-Tregoe, MAUT, AHP, DEX, TOPSIS, PROMETHEE, UTA.

Napredne metode odločitvenega modeliranja: integracija odločitvenih dreves, diagramov vpliva in večkriterijskih modelov, integracija metod analize podatkov in odločitvenega modeliranja, integracija kvalitativnega in
kvantitativnega modeliranja, verjetnostno modeliranje in modeliranje zaupanja, agregacijske funkcije, revizija odločitvenih modelov.

Praktično usposabljanje: praktična uporaba izbranih tehnik in orodij za podporo pri odločanju.

Introduction: decision making and decision support, decision process, components of decision making, taxonomy of decisions, disciplines related to decision making.

Decision analysis: modeling methods and techniques of decision analysis, decision making under risk and uncertainty, decision tables, decision trees, influence diagrams, multi-criteria models, selected multi-criteria modeling methods: Kepner-Tregoe, MAUT, AHP, DEX, TOPSIS, PROMETHEE, UTA.

Advanced decision modeling methods: integration of decision trees, influence diagrams and multi-criteria models, integration of data
mining and decision modeling, integration of qualitative and quantitative modelling, probabilistic and confidence modelling, aggregation functions, decision model revision.

Practical training: practical use of selected decision support techniques and tools.

Temeljna literatura in viri / Readings:

Izbrana poglavja iz naslednjih knjig: / Selected chapters from the following books:
Greco, S., Ehrgott, M., Figueira, J.: Multiple Criteria Decision Analysis: State of the Art Surveys. Springer,
2016. ISBN 978-1-4939-3094-4.
A. Ishizaka, and P. Nemery, Multi-criteria Decision Analysis: Methods and Software. Wiley, 2013. ISBN:
978-1-119-97407-9.
M. Bohanec: Odločanje in modeli. DMFA - založništvo, 1. ponatis, 2012. ISBN 978-961-212-190-7.
Bohanec, M.: DEXi: Program for Multi-Attribute Decision Making, User's Manual, Version 5.04. IJS Report DP-13100, Jožef Stefan Institute, Ljubljana, 2020.

Cilji in kompetence:
Objectives and competences:

Cilj predmeta je spoznati napredne metode, tehnike in sisteme za podporo zahtevnih realnih odločitvenih problemov.

Poudarek je na spoznavanju in obvladovanju naprednih metod odločitvene analize in večkriterijskega modeliranja ter na njihovi uporabi v praksi pri reševanju zahtevnih odločitvenih problemov.

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 advanced methods of decision analysis and multicriteria modeling, and their practical applications for solving complex decision problems.

Predvideni študijski rezultati:
Intendeded learning outcomes:

Študenti bodo z uspešno opravljenimi obveznostmi tega predmeta pridobili:
- razumevanje konceptov odločanja, odločitvenih
procesov in sistemov za podporo pri odločanju,
- razumevanje različnih odločitvenih nalog in
različnih vrst odločitvenih problemov,
- znanja o pristopih odločitvene analize in razumevanje metod odločitvenega modeliranja,
- veščine izdelave odločitvenega modela in njegove uporabe za reševanje realnega odločitvenega problema,
- osnovne veščine uporabe računalniške programske opreme za podporo pri odločanju.

Students successfully completing this course will
acquire:
- understanding the concepts of decision making, decision processes and decision support systems,
- understanding of various decision tasks and
categories of decision problems,
- understanding the approaches of decision analysis and decision modeling,
- the ability to identify decision problems and specify its properties and components,
- the ability to develop and apply a decision model in real-life decision problems,
- basic skills for using decision support and decision modeling software.

Metode poučevanja in učenja:
Learning and teaching methods:

Predavanja, seminar, konzultacije, samostojno delo.

Lectures, seminar, consultations, individual work.

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Pisni ali ustni izpit
50 %
Written or oral exam
Seminarska naloga
25 %
Seminar work
Ustni zagovor seminarske naloge
25 %
Oral defense of the seminar work
Reference nosilca / Lecturer's references:
1. M. Bohanec, Odločanje in modeli: 1. ponatis. DMFA - založništvo, 2012. ISBN 961-212-190-7.
2. Kontić, B., Black, P., French, S., Paulley, A., Zhu, M., Yankovich, T., Webster, M., Pepin, S., Bizjak, T., Bohanec, M.: Demonstrating the use of a framework for risk-informed decisions with stakeholder engagement through case studies for NORM and nuclear legacy sites. Journal of Radiological Protection 42(2) 020504, 2022.
3. Bohanec, M.: From data and models to decision support systems: Lessons and advice for the future. EURO Working Group on DSS: A tour of the DSS developments over the last 30 years (eds. Zaraté, P., Papathanasiou, J., Freire de Sousa, J.), Integrated series in information systems, Cham: Springer, doi: 10.1007/978-3-030-70377-6_11, 191-211, 2021.
4. Bohanec, M., Tartarisco, G., Marino, F., Pioggia, G., Puddu, P.E., Schiariti, M.S., Baert, A., Pardaens, S., Clays, E., Vodopija, A., Luštrek, M.: HeartMan DSS: A decision support system for self-management of congestive heart failure. Expert Systems with Applications 186, 115688}, 2021.
5. Bohanec, M.: DEX (Decision EXpert): A qualitative hierarchical multi-criteria method. Multiple Criteria Decision Making (ed. Kulkarni, A.J.), Studies in Systems, Decision and Control 407, Singapore: Springer, doi: 10.1007/978-981-16-7414-3_3, 39-78, 2022.