PANMIN: sequential and parallel global optimization procedures with a variety of options for the local search strategy We present two sequential and one parallel global optimization codes, that belong to the stochastic class, and an interface routine that enables the use of the Merlin/MCL environment as a non-interactive local optimizer. This interface proved extremely important, since it provides flexibility, effectiveness and robustness to the local search task that is in turn employed by the global procedures. We demonstrate the use of the parallel code to a molecular conformation problem.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Voglis, C.; Lagaris, I.E.: Towards “Ideal multistart”. A stochastic approach for locating the minima of a continuous function inside a bounded domain (2009)
- Blekas, K.; Lagaris, I.E.: Newtonian clustering: an approach based on molecular dynamics and global optimization (2007)
- Tsoulos, Ioannis G.; Lagaris, Isaac E.: Genetically controlled random search: a global optimization method for continuous multidimensional functions (2006)
- Theos, F.V.; Lagaris, I.E.; Papageorgiou, D.G.: PANMIN: sequential and parallel global optimization procedures with a variety of options for the local search strategy (2004)