title: New Tabu Search based global optimization methods outline of algorithms and study of efficiency.
abstract: The study presents two new nonlinear global optimization routines; the Gradient Only Tabu Search (GOTS) and the Tabu Search with Powell's Algorithm (TSPA). They are based on the Tabu-Search strategy, which tries to determine the global minimum of a function by the steepest descent-mildest ascent strategy. The new algorithms are explained and their efficiency is compared with other approaches by determining the global minima of various well-known test functions with varying dimensionality. These tests show that for most tests the GOTS possesses a much faster convergence than global optimizer taken from the literature. The efficiency of the TSPA compares to the efficiency of genetic algorithms.
authors.affiliation: Institut für Organische Chemie, Institut für Chemie, Universität Würzburg, Am Hubland, D-97070 Würzburg.
authors.forename: Svetlana
authors.initials: S
authors.lastname: Stepanenko
authors.forename: Bernd
authors.initials: B
authors.lastname: Engels
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017711:Nonlinear Dynamics