🚀 go-pugleaf

In article <15381@ucdavis.ucdavis.edu> JRBANGA@poppy.ucdavis.edu (JULIO RODRIGUEZ BANGA) writes:
>
> Hi there.
>
>  There is a huge amount of literature reporting the solution of optimization
>problems using genetic algorithms and direct search optimization methods (like
>the Complex from Box) that are more or less 'stochastic'.
> 
> I'm myself a user of this type of methods because they are usually easy to
>work with and, more important, they usually work well, if you don't mind CPU
> time very much. 
>
> However, these methods are usually regarded as 'politically incorrect', and
>considered as 'inferior' when compared with, for example, SQP (sequential
>quadratic programming) and gradient methods. For those interested, see the
>comments of Dr. Sargent in the book 'Foundations of computer-aided process
>design', edited by Sirola, Grossman and Stephanopoulos, CAChE-Elsevier, 1990.
>
> Though my work deals with optimization, I'm not an expert in the field, so I'd
>like to receive opinions about the pros and cons of GA and direct search
>methods when compared with 'politically correct' algorithms. Particularly, 
>if those methods are 'incorrect', why are they so widely used?.

What is "widely used" seems to depend on the field of study. In the
literature that I am familiar with (economics) the Genetic Algorithm 
is not widely used. When used, it seems mainly to be used in order to 
find a starting value for a more conventional algorithm. Or, from the
reverse perspective, the conventional algorithms (gradient based) are 
being used to locally improve the result of the GA.