TY - JFULL AU - Eva Eggeling and Dieter W. Fellner and Torsten Ullrich PY - 2013/2/ TI - Probability of Globality T2 - International Journal of Mathematical and Computational Sciences SP - 35 EP - 40 VL - 7 SN - 1307-6892 UR - https://publications.waset.org/pdf/6040 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 73, 2013 N2 - The objective of global optimization is to find the globally best solution of a model. Nonlinear models are ubiquitous in many applications and their solution often requires a global search approach; i.e. for a function f from a set A ⊂ Rn to the real numbers, an element x0 ∈ A is sought-after, such that ∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application, the question whether a found solution x0 is not only a local minimum but a global one is very important. This article presents a probabilistic approach to determine the probability of a solution being a global minimum. The approach is independent of the used global search method and only requires a limited, convex parameter domain A as well as a Lipschitz continuous function f whose Lipschitz constant is not needed to be known. ER -