The following module was proposed for inclusion in the Module List:
modid: Math::Evol
DSLIP: bdpfp
description: Evolution Search Optimisation
userid: PJB (Peter Billam)
chapterid: 6 (Data_Type_Utilities)
communities:
similar:
Math::Amoeba
rationale:
This module implements the two-membered evolution strategy.
Derivatives of the objective function are not required. Constraints
can be incorporated. It derives from the 'EVOL' Fortran routine of
Schwefel which uses Rechenberg's step- size adjustment strategy.
This two-membered evolution strategy is a random strategy, and as
such is particularly robust and will cope well with large numbers of
variables, or rugged objective funtions. 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. A subroutine is
supplied allowing the evolution of numeric parameters in a text
file. The module Math::Amoeba.pm by John A.R. Williams offers the
Simplex strategy of Nelder and Mead; it is a deterministic strategy
which can offer fast convergence on smaller problems with smooth
objective functions. It doesn't offer an interactive approach.
enteredby: PJB (Peter Billam)
enteredon: Sat Oct 19 05:53:38 2002 GMT
The resulting entry would be:
Math::
::Evol bdpfp Evolution Search Optimisation PJB
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