A scatter search approach for unconstrained continuous optimization

Scatter search is a population based approach founded on ideas of spatial combination augmented by designs for exploiting memory. Introduced contemporaneously with early genetic algorithm proposals, and largely overlooked until recently, scatter search provides a historical bridge between evolutionary procedures and the adaptive memory strategies of tabu search. We exploit this bridge between adaptive memory and evolutionary strategies by developing a simple scatter search approach for optimizing continuous unconstrained functions. Numerical results are reported for the first ICEO test bed functions