This course will enable the students to -
Course Outcomes (COs):
Course |
Learning outcomes (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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MAT 323A |
Advanced Operations Research-I (Theory)
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The students will be able to –
CO81: Identify the optimization techniques suitable for the real time problems. CO82: Describe the theoretical CO83: Explain the concepts of integer programming and discuus different methods of finding solution. CO84: Define the goal programming technique concepts and demonstrate the formulations of real-world situations as linear goal programming problems and describe the solution methods for linear goal programming problems.. CO85: Determine the inventory level of an industry for the smooth functioning for deterministic model with price breaks. CO86: Understand and develop probability inventory models and setting safety stocks
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Approach in teaching:
Interactive Lectures, Discussion, Power Point Presentations, Informative videos
Learning activities for the students: Self learning assignments, Effective questions, presentations, Field trips |
Quiz, Poster Presentations, Power Point Presentations, Individual and group projects, Open Book Test, Semester End Examination
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(Note: Non-Programmable scientific calculator up to 100 MS is permitted)
Revised simplex method: Standard form I and II, Computational procedure, Bounded variable problems in linear programming, Dual simplex method.
Integer linear programming: Gomory’s cutting plane method for all integer and mixed integer, Branch and bound algorithm.
Goal programming: Definition, Formulation and graphical solution of goal programming models, Methodology of solution procedure of goal programming algorithm, Extended simplex method.
Dynamic demand models (IV and V), Deterministic model with price break: one, two and any price break.
Probabilistic inventory models: Instantaneous demand and no set up cost model, Uniform demand and no setup cost model, Probabilistic order level system with constant lead time, Multi period probabilistic model with constant lead time.