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Manuscript Title: Genetically Controlled Random Search: A global optimization method for continuous multidimensional functions.
Authors: Ioannis G. Tsoulos, Isaac E. Lagaris
Program title: GenPrice
Catalogue identifier: ADWP_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 174(2006)152
Programming language: GNU-C++, GNU-C, GNU Fortran - 77.
Computer: The tool is designed to be portable to all systems running the GNU C++ compiler.
Operating system: The tool is designed to be portable to all systems running the GNU C++ compiler.
RAM: 200KB.
Word size: 32
Keywords: Global optimization, stochastic methods, genetic programming, grammatical evolution.
PACS: 02.60.-x, 02.60.Pn, 07.05.Kf, 02.70.Lq, 07.05.Mh.
Classification: 4.9.

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 are frequently trapped in local minima. Global optimization is hence 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)

Solution method:
Grammatical Evolution is used to accelerate the process of finding the global minimum of a multidimensional, multimodal function, in the framework of the original "Controlled Randon Search" algorithm.

Running time:
Depends on the objective function.