Most branch-and-bound algorithms in global optimization depend on convex underestimators to calculate lower bounds of a minimization objective function. The <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$\alpha $$</EquationSource> </InlineEquation>BB methodology produces such underestimators for sufficiently smooth functions by analyzing interval Hessian approximations....</equationsource></inlineequation>

type="main" <p>In this paper, we consider balanced hierarchical data designs for both one-sample and two-sample (two-treatment) location problems. The variances of the relevant estimates and the powers of the tests strongly depend on the data structure through the variance components at each...</p>

In this paper a linear programming-based optimization algorithm called the Sequential Cutting Plane algorithm is presented. The main features of the algorithm are described, convergence to a Karush-Kuhn-Tucker stationary point is proved and numerical experience on some well-known test sets is...