1. SylabUZ
2. Faculty of Mechanical Engineering
3. winter term 2023/2024
4. Management and Production Engineering - Second-cycle studies leading to MSc degree
5. Decision Support Systems

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Decision Support Systems - course description

Aim of the course

Acquisition of skills and competences in decision support system (DSS) and methods used in decision process analysis which are useful in further educational process and vocational work. Also knowledge and skills of chosen tools and technique used in decision support systems will be given.

Prerequisites

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Basic of computer science, probability, statistic

Scope

Lecture:
W1: Introduction to the theory of decision-making. Confidence, risk, uncertainty. 
W2 - W3: Mathematical modeling and decisions, operations research models and econometric statistical decision theory, decision analysis, decision trees. 
W4 - W5: The theory of reliability and usability and decision-making. The decisions in terms of inaccuracy. Game theory and the decisions, game double zero-sum and non-zero; importance of information, cooperative games; negotiations; distribution of payments in the coalition; balance, optimal strategies. Examples of applications in business practice. 
W6 - W7: Decision Support Systems and Information Systems Management, Principles of creation and utilization systems.

Project. Development of the project in the field of production engineering issues, taking into account the theoretical basis and principles of the work program concerning:

- selection of probe items,

- forecasting and linear regression,

- allocation of resources and balancing production lines,

- serial work,

- linear programming, integer and 0-1,

- dynamic programming,

- stock management,

- PERT-CPM,

- modelling network,

- systems queuing,

- simulation of queuing systems

- economy materials

- quality control charts.

Teaching methods

Conventional lecture.

Project – individual work, group work with DSS systems, based on literature and the lecture notes

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

Lecture: graded credit

The assessment is issued based on a written test covering the verification of the knowledge of basic problems.

Project: graded credit

The assessment is determined on the basis of the component evaluating skills related to the implementation of project tasks, the prepared report and a component for the student's "defence" of the report.

Recommended reading

1. Taylor, James (2012). Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics. Boston MA: Pearson Education.
2. Burstein, Frada & Frada, & Holsapple, Clyde & Clide,. (2008). Handbook on Decision Support Systems 1: Basic Themes. 10.1007/978-3-540-48713-5. 
3. Burstein, Frada & Frada, & Holsapple, Clyde & Clide,. (2008). Handbook on Decision Support Systems 2: Variations. 10.1007/978-3-540-48716-6. 
4. Power, D. J. (2002). Decision support systems: concepts and resources for managers. Westport, Conn., Quorum Books.

Further reading

1. Borges, J.G, Nordström, E.-M. Garcia Gonzalo, J. Hujala, T. Trasobares, A. (eds). (2014). " Computer-based tools for supporting forest management. The experience and the expertise world-wide. Dept of Forest Resource Management, Swedish University of Agricultural Sciences. Umeå. Sweden.
2. Delic, K.A., Douillet,L. and Dayal, U. (2001) "Towards an architecture for real-time decision support systems:challenges and solutions.

Notes

Modified by dr Katarzyna Skrzypek (last modification: 19-04-2023 18:15)