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NPTEL

Constrained and unconstrained optimization

NPTEL and Indian Institute of Technology, Kharagpur via YouTube

Syllabus

Lecture 1 : Introduction to Optimization.
Lecture 2 : Assumptions & Mathematical Modeling of LPP.
Lecture 3 : Geometrey of LPP.
Lecture 4 : Graphical Solution of LPP- I.
Lecture 5 : Graphical Solution of LPP- II.
Lecture 6: Solution of LPP: Simplex Method.
Lecture 7: Simplex Method.
Lecture 8: Introduction to BIG-M Method.
Lecture 9: Algorithm of BIG-M Method.
Lecture 10: Problems on BIG-M Method.
Lecture 11: Two Phase Method: Introduction.
Lecture 12: Two Phase Method: Problem Solution.
Lecture 13: Special Cases of LPP.
Lecture 14: Degeneracy in LPP.
Lecture 15: Sensitivity Analysis- I.
Lecture 16: Sensitivity Analysis- II.
Lecture 17: Problems on Sensitivity Analysis.
Lecture 18: Introduction to Duality Theory- I.
Lecture 19: Introduction to Duality Theory- II.
Lecture 20: Dual Simplex Method.
Lecture 21: Examples on Dual Simplex Method.
Lecture 22: Interger Linear Programming.
Lecture 23: Interger Linear Programming.
Lecture 24: IPP: Branch & BBound Method.
Lecture 25: Mixed Integer Programming Problem.
Lecture 26 : Introduction to Transportation Problem - I.
Lecture 27 : Transportation Problem - II.
Lecture 28 : Vogel Approximation Method.
Lecture 29 : Optimal Solution Generation for Transportation Problem.
Lecture 30 : Degeneracy in TP and Overview of Assignment Problem.
Lecture 31 : Introduction to Nonlinear programming.
Lecture 32 : Graphical Solution of NLP.
Lecture 33 : Types of NLP.
Lecture 34 : One dimentional unconstrained optimization.
Lecture 35 : Unconstrained Optimization.
Lecture 36 : Region Elimination Technique-1.
Lecture 37 : Region Elimination Technique-2.
Lecture 38 : Region Elimination Technique-3.
Lecture 39 : Unconstrained Optimization.
Lecture 40 : Unconstrained Optimization.
Lecture 41 : Multivariate Unconstrained Optimization-1.
Lecture 42 : Multivariate Unconstrained Optimization-2.
Lecture 43 : Unconstrained Optimization.
Lecture 44: NLP with Equality Constrained-1.
Lecture 45 : NLP with Equality Constrained-2.
Lecture 46 : Constrained NLP - I.
Lecture 47 : Constrained NLP - II.
Lecture 48 : Constrained Optimization.
Lecture 49 : Constrained Optimization (Contd.).
Lecture 50 : KKT.
Lecture 51 : Constrained Optimization.
Lecture 52 : Constrained Optimization (Contd.).
Lecture 53 : Feasible Direction.
Lecture 54 : Penalty and Barrier Method.
Lecture 55 : Penalty Method.
Lecture 56 : Penalty and Barrier Method.
Lecture 57 : Penalty and Barrier Method (Contd.).
Lecture 58 : Dynamic Programming.
Lecture 59 : Multi - Objective Decision Making.
Lecture 60 : Multi-Attribute Decision Making.

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Constrained and Unconstrained Optimization

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