[R] Combinatorial Optimisation
Adrian Trapletti
adrian.trapletti at lmttrading.com
Fri Oct 25 09:46:21 CEST 2002
> Date: Thu, 24 Oct 2002 08:58:08 +0200 (CEST)
> From: Detlef Steuer <Detlef.Steuer at unibw-hamburg.de>
> Subject: RE: [R] Combinatorial Optimisation
>
> This thread missed me somehow.
>
> If not mentioned before:
> simulated annealing is implemented in optim().
The current implementation of simulated annealing in optim() has been designed for a continuos parameter space. The next candidate
point in the parameter space is generated from a Gaussian Markov kernel with scale proportional to the actual temperature. However,
it is quite simple to change this for a combinatorial optimization:
in the R source tree, see the file src/main/optim.c, function samin:
What you need to change are the four lines, that are responsible for generating a new candidate point:
for (i = 0; i < n; i++)
dp[i] = scale * t * norm_rand(); /* random perturbation */
for (i = 0; i < n; i++)
ptry[i] = p[i] + dp[i]; /* new candidate point */
You could, e.g., replace them by a call to an R function, which randomly selects a new candidate point of a finite set of points.
Hence, to quickly get SA for combinatorial optimization:
Copy and paste samin from optim.c
Change the four lines
Write an R wrapper for this new function
best
Adrian
PS: TO R-DEVEL: What about having this behaviour in optim (default as is, optional a function argument which selects a candidate
point)?
--
Dr. Adrian Trapletti Phone : +41 (0) 1 994 5631
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