Posted by
Peter Caspers-4 on
Nov 22, 2013; 8:58pm
URL: http://quantlib.414.s1.nabble.com/global-optimizers-tp14677.html
Hi,
picking up the topic "global optimization" which was mentioned recently
on the quantlib user conference I added an experimental simulated
annealing optimizer here
https://github.com/lballabio/quantlib/pull/57which is a reimplementation from the one in Numerical Recipes, 2nd ed.
I do not have real use cases at the moment. However I tried it with the
toy example minimizing
f(x,y) = (2.0+sin(x)*sin(y))*(x*x+y*y)
starting at (10,20) with (a rather unfavorable) lambda = 1 for building
the initial simplex. A start temperature of 1000.0 and 500 moves for
cooling down to zero finds the global optimum at (0,0) in 667
iterations. The success is obviously dependent on suitable parameters
though.
DifferentialEvolution which is already available in the library does
also find the minimum. It needs 5900 iterations in my experiment, but
works out of the box with the standard configuration.
best regards
Peter
------------------------------------------------------------------------------
Shape the Mobile Experience: Free Subscription
Software experts and developers: Be at the forefront of tech innovation.
Intel(R) Software Adrenaline delivers strategic insight and game-changing
conversations that shape the rapidly evolving mobile landscape. Sign up now.
http://pubads.g.doubleclick.net/gampad/clk?id=63431311&iu=/4140/ostg.clktrk_______________________________________________
QuantLib-dev mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-dev