Direct search method unconstrained optimization|Lec 3 |nonlinear programming |operations research |
Channel: Mechpro classes
Date: 2020-06-18

In this session we have discussed on different methods of unconstrained optimization techniques for solving nonlinear programming problems. We also discussed on random search and Grid search methods.

A direct search algorithm for numerical search optimization depends on the objective function only through ranking a countable set of function values. It does not involve the partial derivatives of the function and hence it is also called non gradient or zeroth order method.
Unconstrained optimization problems consider the problem of minimizing an objective function that depends on real variables with no restrictions on their values. Mathematically, let x∈Rn be a real vector with n≥1 components and let f:Rn→R be a smooth function. Then, the unconstrained optimization problem is
                                            minxf(x).
Unconstrained optimization problems arise directly in some applications but they also arise indirectly from reformulations of constrained optimization problems. Often it is practical to replace the constraints of an optimization problem with penalized terms in the objective function and to solve the problem as an unconstrained problem.

#operationresearch #unconstrainedoptimization #Mechproclasses #Makaut#directsearchmethod#nonlinearprogramming
#directsearch
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