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- Xref: sparky comp.ai.neural-nets:4617 sci.math.num-analysis:3634 sci.math.stat:2641 sci.physics:21417
- Path: sparky!uunet!usc!elroy.jpl.nasa.gov!nntp-server.caltech.edu!ingber
- From: ingber@cco.caltech.edu (Lester Ingber)
- Newsgroups: comp.ai.neural-nets,sci.math.num-analysis,sci.math.stat,sci.physics
- Subject: Very Fast Simulated Reannealing (VFSR) v6.35 now in Netlib
- Date: 18 Dec 1992 13:48:34 GMT
- Organization: California Institute of Technology, Pasadena
- Lines: 49
- Distribution: world
- Message-ID: <1gskriINN64n@gap.caltech.edu>
- NNTP-Posting-Host: alumni.caltech.edu
-
- Very Fast Simulated Reannealing (VFSR) v6.35
-
- Netlib requested an early update, and VFSR v6.35 is now in Netlib
- and soon will be updated in Statlib. The code is stable, and is
- being used widely. The changes to date typically correct typos and
- account for some problems encountered on particular machines.
-
- NETLIB
- Interactive:
- ftp research.att.com
- [login as netlib, your_login_name as password]
- cd opt
- binary
- get vfsr.Z
- Email:
- mail netlib@research.att.com
- send vfsr from opt
-
- STATLIB
- Interactive:
- ftp lib.stat.cmu.edu
- [login as statlib, your_login_name as password]
- cd general
- get vfsr
- Email:
- mail statlib@lib.stat.cmu.edu
- send vfsr from general
-
- EXCERPT FROM README
- 2. Background and Context
-
- VFSR was developed in 1987 to deal with the necessity of
- performing adaptive global optimization on multivariate nonlinear
- stochastic systems[2]. VFSR was recoded and applied to several
- complex systems, in combat analysis[3], finance[4], and neuro-
- science[5]. A comparison has shown VFSR to be superior to a
- standard genetic algorithm simulation on a suite of standard test
- problems[6], and VFSR has been examined in the context of a
- review of methods of simulated annealing[7]. A project comparing
- standard Boltzmann annealing with "fast" Cauchy annealing with
- VFSR has concluded that VFSR is a superior algorithm[8]. A paper
- has indicated how this technique can be enhanced by combining it
- with some other powerful algorithms[9].
-
- --
- || Prof. Lester Ingber [10ATT]0-700-L-INGBER ||
- || Lester Ingber Research Fax: 0-700-4-INGBER ||
- || P.O. Box 857 Voice Mail: 1-800-VMAIL-LI ||
- || McLean, VA 22101 EMail: ingber@alumni.caltech.edu ||
-