Genetically controlled random search: a global optimization method for continuous multidimensional functions

Published: 15 January 2006| Version 1 | DOI: 10.17632/kswtxrswbr.1
Ioannis G. Tsoulos, Isaac E. Lagaris


Abstract A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use of the procedure known as grammatical evolution. The method can be considered as a “genetic” modification of the Controlled Random Search procedure due to Price. The user may code the objective function either in C++ or in Fortran 77. We offer a comparison of the new method with others of similar structure, by presen... Title of program: GenPrice Catalogue Id: ADWP_v1_0 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 d ... Versions of this program held in the CPC repository in Mendeley Data ADWP_v1_0; GenPrice; 10.1016/j.cpc.2005.09.007 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)



Computational Physics, Computational Method