Several variants of an outer approximation method are proposed to solve truss topology optimization problems with discrete design variables to proven global optimality. The objective is to minimize the volume of the structure while satisfying constraints on the global stiffness of the structure...

A wind turbine rotor blade, based on the U.S. National Renewable Energy Laboratory (NREL) 5 MW reference turbine, is optimized for minimum cost of energy through simultaneous consideration of aerodynamics and bend-twist coupling. Eighty-three total design variables are considered, encompassing...

In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two convex terms: one is smooth and given by a black-box oracle, and another is general but simple and its structure is known. Despite to the bad properties of the sum,...

A framework is presented for the automated superstructure generation and optimization of distributed energy supply systems (DESS). Based on a basic problem description (specifying load cases, available technologies, and topographic constraints), the presented framework first employs the P-graph...

A novel approach is proposed for the superstructure-free synthesis and optimization of distributed energy supply systems (DESS) by exploiting the nature of evolutionary algorithms. Current approaches require the designer to define a superstructure, which subsequently is optimized. In the...

In this paper we extend the smoothing technique [7], [9] onto the problems of Semidefinite Optimization. For that, we develop a simple framework for estimating a Lipschitz constant for the gradient of some symmetric functions of eigenvalues of symmetric matrices. Using this technique, we can...

In this paper we introduce a new primal-dual technique for convergence analysis of gradient schemes for non-smooth convex optimization. As an example of its application, we derive a primal-dual gradient method for a special class of structured non-smooth optimization problems, which ensures a...

In this paper we study the Riemannian length of the primal central path computed with respect to the local metric defined by a self-concordant function. We show that despite to some examples, in many important situations the length of this path is quite close to the length of geodesic curves. We...

In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex optimization. It is based on a special smoothing technique, which can be applied to the functions with explicit max-structure. Our approach can be considered as an alternative to black-box...