The objective of this course is to acquaint the students with the use of operations research techniques in decision-making.
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Paper Code |
Paper Title |
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ABF 401 |
Models of Operations Research |
CO140:Discriminate the characteristics of different types of decision-making environments and the appropriate decision making approaches and tools to be used in each type. CO141:Formulate the mathematical tools that are needed to solve optimization problems.
CO142:Students will design and solve transportation Models and assignment models.
CO143:Persuade the best strategy using decision making methods under uncertainty and game theory.
CO144:Design new simple models, like: CPM, PERT to improve decision –making and develop critical thinking and objective analysis of decision problems. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, Team teaching
Learning activities for the students: Self learning assignments, Effective questions, Seminar presentation, Giving tasks. |
Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects
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Operations Research: Basic Concepts and Definitions, merits and demerits, Techniques of operations research, role of operations research, application areas of operations research.
Linear Programming: Mathematical formulation of Linear Programming problems and their solution using Graphic approach and Simplex method, Duality.
Transportation: Solving the problem. Testing the optimality using MODI method. Cases of unbalanced problems, Degeneracy, Maximization objective.
Assignment: Solving the problem, Cases of unbalanced problems, multiple optimum solutions, maximization objective.
PERT/CPM: Network with one estimate of time, Networks with three estimates of time, Time-cost trade-off, Probability consideration under PERT.
Game Theory: Games of Pure strategy, Games of Mixed strategy, Law of Dominance, Sub Game method.
Queuing Theory: Meaning, features, elements of queuing theory, queuing system, Single Channel Queuing Problem
Decision Theory: Maximin, Minimax, and Maximax expected pay off and regret, Expected value of Perfect Information.
Simulation- Meaning, Phases and Applications. Monte-Carlo Method – Concept & Steps.