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Sem 7 -OPTIMIZATION TECHNIQUES (SELECTIVE – 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.
References
S.S. Rao, Optimization theory and application, New Age International P. Ltd.
2. A.D. Belegundu, T.R. Chandrupatla, Optimization Concepts and applications in Engineering, Pearson Education Asia.
F. S. Budnick, D. McLeavey, R. Mojena, Richard D, Principles of Operations Research for Management, Irwin, INC.
H. A. Taha, Operation Research an introduction, Eastern Economy Edition.
R. Panneerselvam, Operations Research, PHI.
mg university b.tech s7 civil syllabus