Numerical Optimization ( norm minim)

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Homework Help Overview

The problem involves finding the point in a defined half space that minimizes the Euclidean norm. The half space is characterized by a linear inequality involving a vector and a scalar. The optimization task is to formulate this problem mathematically and explore potential solutions.

Discussion Character

  • Exploratory, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the formulation of the optimization problem, questioning the correctness of the initial setup. There is exploration of geometric interpretations related to the intersection of a plane and a set defined by a norm constraint. Some participants suggest considering tangents and normals in relation to the problem.

Discussion Status

Participants are actively engaging with the problem, with some providing mathematical expressions and reasoning. There is acknowledgment of the use of Lagrange multipliers, although clarity on vector notation is noted as a challenge. The discussion reflects a mix of interpretations and approaches without reaching a consensus.

Contextual Notes

There are indications of potential confusion regarding vector notation and the geometric implications of the problem setup. The participants are navigating through the constraints and definitions involved in the optimization task.

sbashrawi
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Homework Statement



Consider the half space defined by H = {x ∈ IRn | aT x +alpha ≥ 0} where a ∈ IRn
and alpha ∈ IR are given. Formulate and solve the optimization problem for finding the point
x in H that has the smallest Euclidean norm.

Homework Equations





The Attempt at a Solution


I need help in this problem. I think the problem can be written as

min ||x|| sunbjected to a(transpose) x + a >= 0

am I right
 
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consider the set [itex]\left\{ x \in \mathbb{R}^n : ||x||^2 = c\}[/itex] for some constant c, geometrically what does it represent?

now consider the half space, the boundary of which is a plane. how does the plane intersect the above set, in particular for the minimum value of c. This should lead to a simple solution
 
hint: think tangents & normals
 
Here is my work:

f(x) = ||x|| ^2
subjeted to c(x) = a^{T} x +[tex]\alpha[/tex][tex]\geq[/tex]0

so L ( x,[tex]\lambda[/tex]) = f(x) - [tex]\lambda[/tex] c(x)
gradiant L(x,[tex]\lambda[/tex]) = 2x - [tex]\lambda[/tex] grad(c(x)) = 0
grad c(x)= a
so 2x - [tex]\lambda[/tex]a = 0
this gives that x = [tex]\frac{}{}[1/2]\lambda[/tex]a
and
c(x) = 0
gives : [tex]\lambda[/tex] = -2 [tex]\alpha[/tex][tex]/ ||a||^2<br /> <br /> imlpies <br /> <br /> x = - \alpha[/tex] a / ||a||^2
 
Lagrange multipliers ok,, though bit hard to read what is a vector

the answer makes sense to me as the boundary plane will have a as its normal, and the answer is both on the boundary plane & parallel to a
 

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