[ROOT] libOptimization build 18.12.2000 released

From: FOKIN@tsl.uu.se
Date: Mon Dec 18 2000 - 23:04:34 MET


Hi people,

libOptimization 1.0 build 18.12.00 has been released.
You can grab it at

  http://svedaq.tsl.uu.se/~anton/neural.html

the lib includes:

	* Simulated annealing
	* Genetic algorithm (interface to GAlib from MIT)
	* Coordinate descent

It can be used to minimize TF1 and TF2 or any object
derived from TOptimizable class. 

The package includes two examples on TF1 and TF2 minimization 
(sin(x)/x alike).

Simulated annealing algorithm is modified to easily solve
different combinatorial optimization problems, for example to
find the best subset of N items from M item universe according
to a (non-quadratic) objective (cost) function. 

Examples of real-word applications, such as portfolio/trading strategy
optimization can be found on the R-Quant web site. The algorithm has shown 
quite good performance selecting the best 40 stock portfolio from 1.500 stocks 
presented on the market in a reasonable time of a few minutes/tens of minutes 
(depending on a desired error tolerance). The objective function of this
1.500 parametric problem with C(N,M) local minima included step-wise/ 
non-quadratic transaction costs.

On the R-Quant web site you can also find some theory and references
about simulated annealing and its modifications.

Note : If you compile libNeural with libOptimization,
you can train nets with the algorithms above. Although
stochastic training is usually (much) slower than conventional gradient 
propagational methods, it guarantees that the net ends up in the global
minimum of its error function. Thus, for example, a net can be
trained to solve spiral separation problem (two classes of points
on 2D plane separated with a spiral border). This can be in
no way achieved with backprop or its modifications.

libOptimization is a part of R-Quant Data Analysis
Studio. Several screenshots of a new Qt based
IDE is available on the site. 

libNeural and libOptimization classes can not be used in any 
commercial project or non-scientific environment without
written permission ganted by the author.

If you use these classes in the data analysis, etc., 
please let me know to stimulate further development
in right direction.

/Anton



This archive was generated by hypermail 2b29 : Tue Jan 02 2001 - 11:50:39 MET