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Code IE 415
Term 201602
Title Decision Support Systems
Faculty Faculty of Engineering and Natural Sciences
Subject Industrial Engineering(IE)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Guvenc Sahin,
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
(only for SU students)
IE301 MS301 CS201
Mode of Delivery Interactive lecture
Planned Learning Activities Interactive,Learner centered,Communicative,Discussion based learning,Project based learning,Task based learning,Guided discovery,Case Study

A Decision Support System is the marriage of Information Technology and Operations Research. A typical DSS includes a database, a model base, a knowledge base and a graphical user interface (GUI). The course includes a brief introduction of database management systems (relational databases, SQL), optimization techniques, spreadsheet based optimization, and review of relevant AI techniques that would be crucial to develop the model base; knowledge acquisition and knowledge representation, probabilistic and approximate reasoning as the basis of the knowledge base and GUI development. The course will also include the discussion of DSSs for a number of application domains, chosen to illustrate principles of system development, such as the health care applications, portfolio optimization, production and distribution systems, and information systems for top management. The learning outcome of the course is to learn how to couple the IT tools with the optimization tools in real world problems, particularly in manufacturing and service systems.


The course aims to deliver the necessary computing skills to IE students so that they can demonstrate their knowledge on operational research techniques and operations management problems by developing a software package that assists the decision makers.

Learning Outcome

List the basic components of a decision support system (DSS) along with their functionalities
Use (MS Excel) basic spreadsheet features, functions and methods to develop a completely spreadsheet-based DSS
Apply advanced (MS Excel) spreadsheet functions to further enhance the level of interactivity and the information flow between the user and the interface of DSS
Use MS Excel applications such as Solvers and Data Analysis Toolbox within sample DSS implementations with a knowledge and/or model base to elevate level of intelligence and analysis capabilities of the system
Make use of MS Excel VBA as a programming language to demonstrate how basic programming structures and functionalities my be coded using both the spreadsheet and interactive interface tools
Make use of MS Excel VBA as a programming language to implement MS Excel tools such as Solvers and Data Analysis
Toolbox within sample DSS implementations with a knowledge and/or model base
Design and create a graphical user interface via user forms for a DSS application
Design a DSS application as a case study involving complex operations management and operations research problems

Programme Outcomes
Common Outcomes For All Programs
1 Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2
2 Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4
3 Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 4
4 Communicate effectively in Turkish and English by oral, written, graphical and technological means. 2
5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 5
Common Outcomes ForFaculty of Eng. & Natural Sci.
1 Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 3
2 Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 4
3 Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 5
4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4
5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 2
6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 1
7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 1
Industrial Engineering Program Outcomes Core Electives
1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 5
2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 4
3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 5
Molecular Biology, Genetics and Bioengineering Program Outcomes Area Electives
1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1
2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1
Materials Science and Nano Engineering Program Outcomes Area Electives
1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1
2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1
3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1
Computer Science and Engineering Program Outcomes Area Electives
1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 5
2 Demonstrate knowledge of discrete mathematics and data structures. 2
3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 3
Assessment Methods and Criteria
  Percentage (%)
Final 25
Midterm 20
Assignment 25
Participation 10
Group Project 20
Recommended or Required Reading

Michelle M. Hanna, Ravinra Ahuja, Wayne L. Winston - Developing Spread Sheet Based Decision Support Systems