Bounds on eigenvalues of real symmetric interval matrices for αBB method in global optimization

In this paper, we investigate bounds on eigenvalues of real symmetric interval matrices. We present a method that computes It outperforms many methods developed in the literature and produces as sharp possible The aim is to apply proposed compute lower hessian matrix nonconvex function ?BB use them produce tighter underestimator improves algorithm for solving global optimization problems. end, illustrate by example, comparison various approaches bounding Moreover, set test problems found are solved efficiently performances compared with those other methods.