A new multisection technique in interval methods for global optimization

A new multisection technique in interval methods for global optimization is investigated, and numerical tests demonstrate that the efficiency of the u nderlying global optimization method can be improved substantially. The heu ristic rule is based on experiences that suggest the subdivision of the cur rent subinterval into a larger number of pieces only if it is located in th e neighbourhood of a minimizer point. An estimator of the proximity of a su binterval to the region of attraction to st minimizer point is utilized. Ac cording to the numerical study made, the new multisection strategies seem t o be indispensable, and can improve both the computational and the memory c omplexity substantially.