OPTIMIZATION - THEORY AND APPLICATIONS
Group A

Introduction to optimisation: Historical development. Engineering applications. Statement of
an optimisation problem, classification and formulation of optimisation problems,
optimisation techniques.
Classical optimisation methods: Single variable optimisation, multivariable optimisation with and without constraints.
Linear programming: Standard form of a linear programming problem (LPP), geometry of
LPPs, related theorems, linear simultaneous equations, pivotal reduction, simplex method,
revised simplex method, duality, decomposition, transportation and assignment problems.
Nonlinear programming (unconstrained): Uni-modal function, exhaustive search, bi-section
and golden section methods, interpolation methods, random search methods, univariate
method, gradient of a function, conjugate gradient, quasi-Newton and variable metric
methods.



Group B

 

Nonlinear programming (constrained): Complex method* cutting plane method, method of
feasible directions, transformation techniques, penalty function methods, convergence
checks.
Geometric programming: Introduction to geometric programming, polynomial, unconstrained
and constrained problems.
Dynamic programming: Introduction to dynamic programming, multistage decision
processes, computational procedures, calculus and tabular methods.





 

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