As a
starting point I have prepared
a brief
overview of simulated annealing, using
some of the sources
further on.
A name which crops up frequently
in simulated annealing is that of
Lester Ingber. His site
is a
comprehensive resource of papers and simulated
annealing software.
More tweaks by Ingber: Adaptive
Simulated
Annealing (ASA) is a global optimisation
algorithm based on an
associated
proof that
the parameter space can
be sampled much more
efficiently than by using other
previous
simulated
annealing algorithms,
while in Very Fast
Simulated Re-Annealing, the introduction
of re-annealing permits
adaptation to
changing
sensitivities in the
multi-dimensional
parameter-space and speeds
things up.
While his paper Simulated
annealing: Practice versus theory is
ostensibly on demonstrating
how simulated
quenching
can be much faster
than simulated annealing
without sacrificing
accuracy, it is
an extremely wide-ranging and
comprehensive
paper
which covers a variety of
techniques and
applications and also
provides almost a
hundred references.
Recommended.
A paper by Frost and
Heineman
provides an
insight into a
heuristic
for parallel
stochastic optimisation
|
(May
take a
while to
download these
PDFs)
Applications
to
investment problems are addressed in A simple options
training model, which reveals some simple
but relevant
probabilistic insights into the
nature of
options
trading often not discussed in most texts, and
Trading Markets With Canonical
Momenta
and Adaptive Simulated
Annealing
a short
but interesting article
on intuition versus analysis.
The paper Mortgage
Pool Allocation by
Simulated Annealing
shows a successful
application of simulated annealing to the
problem of mortgage
pool allocation: it
finds
good (highly profitable) solutions very
quickly. This
result is significant both for
the complexity
of the
problem solved and
because demonstrates the
feasibility of simulated annealing for solving
a real-world
financial
problems. |
The
University of East Anglia KDD
site
has used heuristics (GA,SA,TS) as their main
approach to solving
data mining problems;
so
far they have been most successful with SA.
One of the areas
they first found success with
was the
financial
services sector. Links
and papers related to
this work are on this site.
The
only commercial
source of simulated annealing software
I've
found is Exatech's XSolver, an
Excel add-in.
Haven't
tried it; can't
vouch for it. Their
home page has a Java applet demonstrating the
process of simulated
annealing and the user
manual can be
browsed.
Lester Ingber's ASA code can be
downloaded from his site. Read
the read-me here
first.
The following Fortran code (Word for
easy cutting and pasting) implementation of
simulated annealing was
used in "Global
Optimization of Statistical
Functions with
Simulated Annealing," Goffe,
Ferrier and
Rogers, Journal of Econometrics,
vol. 60,
no. 1/2,
Jan./Feb. 1994, pp. 65-100.
It was
found
competitive, if not superior, to multiple
restarts of
conventional optimisation
routines for
difficult optimisation problems.
Another non-commercial software site is
Taygeta
Scientific Inc |