The continuous reactive tabu search :

A novel algorithm for the global optimization of functions (C-RTS) is presented, in which a combinato-rial optimization method cooperates with a stochastic local minimizer. The combinatorial optimization component, based on the Reactive Tabu Search recently proposed by the authors, locates the most promising \boxes," where starting points for the local minimizer are generated. In order to cover a wide spectrum of possible applications with no user intervention, the method is designed with adaptive mechanisms: the box size is adapted to the local structure of the function to be optimized, the search parameters are adapted to obtain a proper balance of diversiication and intensiication. The algorithm is compared with some existing algorithms, and the experimental results are presented for a suite of benchmark tasks.