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Sem 7 - OPTIMIZATION TECHNIQUES (ELECTIVE – I)

Module1  Classical optimization techniques
Single variable optimization – Multivariable optimization with no constraints – Hessian matrix – Multivariable saddle point – Optimization with equality constraints – Lagrange multiplier method – Multivariable optimization with inequality constraints – Kuhn-Tucker conditions.
Module 2  One-dimensional unconstrained minimization
Elimination methods – unrestricted search method – Fibonacci method – Interpolation methods – Quadratic interpolation and cubic interpolation methods.
Module 3  Unconstrained minimization
Gradient of a function – Steepest descent method – Newton’s method – Powells method – Hooke and Jeeve’s method.
Module 4   Integer – Linear programming problem
Gomory’s cutting plane method – Gomory’s method for all integer programming problems, mixed integer programming problems.
Module 5  Network Techniques
Shortest path model – Dijkstra`s Algorithm – Floyd`s Algorithm – minimum spanning tree problem – PRIM algorithm – Maximal Flow Problem algorithm.
mgu university b.tech syllabus electronics
References
1. Optimization theory and application: S.S. Rao, New Age International P. Ltd.
2. Optimization Concepts and applications in Engineering: A. D. Belegundu, T.R. Chandrupatla, Pearson Education Asia.     
3. Principles of Operations Research for Management: F. S. Budnick, D. McLeavey, R. Mojena, Richard D. Irwin, INC.
4. Operation Research an introduction: H. A. Taha, Eastern Economy Edition.
5. Operations Research: R. Panneerselvam, PHI