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)

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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. 1. Analyzes, compares, and synthesizes advanced theoretical and applied knowledge in subfields of civil engineering.
2. 2. Identifies a problem in the field, formulates a research question, collects and analyzes data, and draws conclusions using scientific methods.
3. 3. Develops innovative solutions by applying modeling, analysis, and interpretation skills to complex engineering problems.
4. 4. Designs new systems, processes, or materials by considering real-world constraints such as economy, environment, sustainability, and safety.
5. 5. Plans laboratory or field studies, collects data, performs statistical analysis, and derives scientific results.
6. 6. Effectively uses modern analysis and design software, information technologies, and measurement tools in civil engineering applications.
7. 7. Recognizes, interprets, and integrates relationships between civil engineering and other engineering or scientific disciplines.
8. 8. Acts in accordance with ethical principles, demonstrates professional responsibility, and evaluates the societal impacts of engineering practices.
9. 9. Communicates research and engineering outcomes clearly and effectively through written, oral, and visual means.
10. 10. Works effectively in intra- and interdisciplinary teams and assumes leadership roles when necessary.
11. 11. Follows, critically evaluates, and continuously improves professional knowledge and skills through lifelong learning.
12. 12. Evaluates the environmental, sustainability, and societal impacts of engineering practices and develops responsible solutions.

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