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<h3 class="section">1.17 Linesearch, minimize a function along dx</h3>
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<h4 class="subheading">Helptext:</h4>
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<pre class="verbatim">[a,fx,nev] = line_min (f, dx, args, narg, h, nev_max) - Minimize f() along dx
INPUT ----------
f : string : Name of minimized function
dx : matrix : Direction along which f() is minimized
args : cell : Arguments of f
narg : integer : Position of minimized variable in args. Default=1
h : scalar : Step size to use for centered finite difference
approximation of first and second derivatives. Default=1E-3.
nev_max : integer : Maximum number of function evaluations. Default=30
OUTPUT ---------
a : scalar : Value for which f(x+a*dx) is a minimum (*)
fx : scalar : Value of f(x+a*dx) at minimum (*)
nev : integer : Number of function evaluations
(*) The notation f(x+a*dx) assumes that args == {x}.
Reference: David G Luenberger's Linear and Nonlinear Programming
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