|File Search||Catalog||Content Search|
This evolution search strategy is a random strategy, and as such is particularly robust and will cope well with large numbers of variables or rugged objective funtions. It derives from the 'EVOL' Fortran routine of Schwefel, which uses Rechenberg's work on step-size adjustment.
Evol.pm works either automatically with an objective function to be minimised, or interactively with a (suitably patient) human who at each step will choose the better of two (or several) possibilities.
Math::Evol This module implements the evolution search strategy. Derivatives of the objective function are not required. Constraints can be incorporated. The caller must supply initial values for the variables and for the initial step sizes. This evolution search strategy is a random strategy, and as such is particularly robust and will cope well with large numbers of v more»
PS_EVOL(1) User Contributed Perl Documentation PS_EVOL(1) NAME ps_evol - Perl script to fine-tune A4 PostScript drawings SYNOPSIS vi plant.ps ps_evol plant.ps > p2.ps DESCRIPTION ps_evol is mainly intended as a demo script illustrating the text_evol funtion in Math::Evol.pm. It assumes you have something like GhostView which allows you t more»
Evol(3) User Contributed Perl Documentation Evol(3) NAME Math::Evol - Evolution search optimisation SYNOPSIS use Math::Evol; ($xbref,$smref,$fb,$lf) = evol(\@xb,\@sm,\&function,\&constrain,$tm); # or ($xbref, $smref) = select_evol(\@xb,\@sm,\&choose_best,\&constrain); # or $new_text = text_evol($text, \&choose_best_text, $ more»
20021019 Math-Evol-1.00 Evolution Search Optimisation 20021020 right version in Install, some doc fi more»