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.