Learning Outcomes |
Learning and teaching strategies |
Assessment |
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After the completion of the course the students will be able to: CLO63- Identify the optimization techniques suitable for the real time problems. CLO64- Solve linear programming by Revised simplex method and solve integer programming also. CLO65- Solve goal programming problems, multi-objective programming problems. CLO66- Compare Determine the inventory level of an industry for the smooth functioning. CLO67- Understand the concept of probability inventory problems. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, Reading assignments, Demonstration, Team teaching Learning activities for the students: Self learning assignments, Effective questions, Simulation, Seminar presentation, Giving tasks, Field practical
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Presentations by Individual Students. Class Tests at Periodic Intervals. Written assignment(s) Semester End Examination |
Revised simplex method: Standard form I and II, Computational procedure, Bounded variable problems in linear programming, Dual simplex method.
Integer linear programming:Gomory’scutting 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 (IVand 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, Multiperiod probabilistic model with constant lead time.
Links:
[1] https://maths.iisuniv.ac.in/courses/subjects/advanced-operations-research-i-optional-paper-0
[2] https://maths.iisuniv.ac.in/academic-year/2019-2020