Programs in Physics & Physical Chemistry
|[Licence| Download | New Version Template] adwu_v2_0.tar.gz(213 Kbytes)|
|Manuscript Title: MinFinder v2.0: An improved version of MinFinder|
|Authors: Ioannis G. Tsoulos, Isaac E. Lagaris|
|Program title: MinFinder v2.0|
|Catalogue identifier: ADWU_v2_0|
Distribution format: tar.gz
|Journal reference: Comput. Phys. Commun. 179(2008)614|
|Programming language: GNU C++, GNU FORTRAN, GNU C.|
|Computer: The program is designed to be portable to all systems running the GNU C++ compiler.|
|Operating system: Linux, Solaris, FreeBSD.|
|RAM: 200000 bytes|
|Keywords: Global optimization, stochastic methods, Monte Carlo, clustering, region of attraction.|
|PACS: 02.60.-x, 02.60.Pn, 07.05.Kf, 02.70.Lq.|
Does the new version supersede the previous version?: Yes
Nature of problem:
A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be trapped in any local minimum. Global optimization is then the appropriate tool. For example, solving a non - linear system of equations via optimization, one may encounter many local minima that do not correspond to solutions, i.e. they are far from zero.
Using a uniform pdf, points are sampled from a rectangular domain. A clustering technique, based on a typical distance and a gradient criterion, is used to decide from which points a local search should be started. Further searching is terminated when all the local minima inside the search domain are thought to be found. This is accomplished via three stopping rules: the "double box" stopping rule, the "observables" stopping rule and the "expected minimizers" stopping rule.
Reasons for new version:
The link procedure for source code in Fortran 77 is enhanced, two additional stopping rules are implemented and a new criterion for accepting-start points, that economizes on function and gradient calls, is introduced.
Summary of revisions:
A technical report describing the revisions, experiments and test runs is packaged with the source code.
Depending on the objective function.
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