




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): Unimodal function, exhaustive search, bisection
and golden section methods, interpolation methods, random search methods, univariate
method, gradient of a function, conjugate gradient, quasiNewton 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.







© Copyright 2008. All right reserved  AMIE Students


