Learning Outcomes |
Learning and teaching strategies |
Assessment |
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After the completion of the course the students will be able to: CLO114- Understand and Solve Replacement problems. CLO115- To derive the necessary conditions (KT conditions) for constrained nonlinear optimization problems and able to solve quadratic programming problems. CLO116- Derive methods to solve separable, geometric programming problems. CLO117- Discuss various methods to solve linear fractional programming problems and dynamic programming problems. CLO118- Explain problems related to sequencing and PERT-CPM to solve network analysis 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 |
Replacement models:Gradual failure, Sudden failure, Replacement due to efficiency deteriorate with time, Staffing problems, Equipment renewal problems.
Nonlinear Programming: Formulation and graphical method for unconstrained problem of maxima and minima,Constrained problem of maxima and minimaLagrangian method, Khun-Tucker condition.Quadratic programming: Wolf and Beals method.
Separable programming: Definition, Reduction to separable programming problem to LPP, Separable programming algorithm. Geometric programming: Formulation and solution of GPP(Unconstraint type and with quality constraint).
Linear fractional programming: Definition, Linear fractional algorithm, Computational procedure of fractional algorithm.Dynamic programming: Introduction, Bellman principle of optimalitymodel –I, II and III, Solution of LPPby dynamic programming.
Network Scheduling by PERT-CPM, Network logical sequencing, Concurrent activities,Critical path analysis, Probability consideration in PERT, Distinction between PERT and CPM