OPERATIONS RESEARCH TECHNIQUES

Course Description

Introduce students to developed techniques, methodologies and models used in Operations Research (OR). Operations Research (or Management Science) is a field of Applied Mathematics that uses mathematical methods and computers to make rational decisions in solving a variety of optimization problems. Most OR techniques require the use of computer software to solve large, complex problems in industry, business, science and technology, management, decision support and other areas and disciplines. In this course Deterministic Problems are considered – the data and future outcomes are known with certainty. Optimization of the solution is the primary goal. Matlab and Excel are used for representing and solving the problems.

OPERATIONS RESEARCH TECHNIQUES

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 Formulate a real-world problem as a mathematical programming model. Implement and solve the model in EXCEL and LINDO.
2. 02 Understand the theoretical workings of the simplex method for linear programming and perform iterations of it by hand
3. 03 Perform sensitivity analysis to determine the direction and magnitude of change of a model’s optimal solution as the data change.
4. 04 Solve specialized linear programming problems like the transportation and assignment problems.Solve network models like the shortest path, minimum spanning tree, and maximum flow problems.
5. 05 Understand the applications of, basic methods for, and challenges in integer programming and other programming

Course Syllabus

Reference Books & Course Materials

1. 01 A Handbook on Multi-Attribute Decision-Making Methods, Wiley Series in Operations Research and Management Science, 2021
2. 02 Multiple Attribute Decision Making Methods and applications, Gwo-Hshiung Tzeng Jih-Jeng Huang, CRC Press Taylor & Francis Group, 2011
3. 03 New Methods and Applications in Multi-Attribute Decision-Making, Alireza Alinezhad, Springer

Learning Outcomes

1. L01 Define quantitative and qualitative attributes SOLO 2
2. L02 Calculate normalized matrices and weights of attributes SOLO 2
3. L03 Develop a decision-making problem considering alternatives, attributes and sub-attributes. SOLO 5
4. L04 Compute decision-making problems using decision-making methods. SOLO 3

Program Outcomes

1. Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
2. Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
3. Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
4. Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
5. Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
6. Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
7. dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
8. Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
9. Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
10. Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
11. Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
12. Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.

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