OPERATIONS RESEARCH I

Course Description

This course is designed to introduce the fundamentals of operations research.Operations Research (OR) refers to the science of decision making. This course provides a survey of fundamental methods of Operations Research and their applications at an introductory level. The emphasis is on applications rather than the details of methodology. By the end of the course, students will be exposed to a wide variety of applications and problems that can be addressed using Operations Research techniques. The emphasis is on solution of deterministic optimization models. The topics covered are application of scientific methodology to business problems, systems concept, team concept in problem analysis, and mathematical modeling. Basic deterministic methods used in the course are linear programming, simplex method, duality, dual simplex method.

OPERATIONS RESEARCH I

Evaluation Tools (Active Term)

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 nderstand the applications of, basic methods for, and challenges in integer programming

Course Syllabus

Reference Books & Course Materials

1. 01 Wayne L. Winston, Operations Research: Applications and Algorithms, 4th ed., Duxbury Press, 2004. ISBN: 0-534-42362-0
2. 02 Taha, Hamdy A., Operations Research, 6th ed., Prentice Hall, 1997.
3. 03 Hillier, F.S. and Lieberman, G.J., Introduction to Operations Research, 7th ed., McGraw Hill, 2001

Learning Outcomes

1. L01 Formulate a real-world problem as a mathematical programming model. Implement and solve the model in EXCEL and LINDO. SOLO 3
2. L02 Understand the theoretical workings of the simplex method for linear programming and perform iterations of it by hand SOLO 4
3. L03 Perform sensitivity analysis to determine the direction and magnitude of change of a model’s optimal solution as the data change. SOLO 4
4. L04 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. SOLO 2
5. L05 understand the applications of, basic methods for, and challenges in integer programming SOLO 4

Program Outcomes

1. P01 Knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline.
2. P02 Ability to apply knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline to the solution of complex engineering problems.
3. P03 Ability to define complex engineering problems by using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) related to the problem addressed.
4. P04 Ability to formulate complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
5. P05 Ability to analyse and solve complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
6. P06 Ability to design creative solutions to complex engineering problems.
7. P07 Ability to design complex systems, processes, devices, or products in a way that meets present and future needs while considering realistic constraints and conditions.
8. P08 Ability to select and use appropriate techniques and resources—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
9. P09 Ability to select and use modern engineering and computational tools—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
10. P10 Ability to conduct literature research and use appropriate research methods for the investigation of complex engineering problems.
11. P11 Ability to design experiments for the investigation of complex engineering problems.
12. P12 Ability to conduct experiments, collect data, analyse results, and interpret findings for the investigation of complex engineering problems.
13. P13 Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the framework of the United Nations Sustainable Development Goals (SDGs).
14. P14 Awareness of the legal implications of engineering solutions within the framework of the United Nations Sustainable Development Goals (SDGs).
15. P15 Knowledge of ethical responsibility and adherence to the principles of professional engineering conduct.
16. P16 Awareness of acting impartially without discrimination in any matter and of being inclusive of diversity.
17. P17 Ability to work effectively as an individual.
18. P18 Ability to work effectively as a team member or leader in intra-disciplinary teams (face-to-face, remote, or hybrid).
19. P19 Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote, or hybrid).
20. P20 Ability to communicate effectively in spoken form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
21. P21 Ability to communicate effectively in written form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
22. P22 Knowledge of professional practices such as project management and economic feasibility analysis.
23. P23 Awareness of entrepreneurship and innovation.
24. P24 Ability for independent and lifelong learning.
25. P25 Ability to adapt to new and emerging technologies.
26. P26 Lifelong learning ability that includes the capacity to think critically about technological changes.

Po-Lo Matrix