We investigate the implementation of a new stochastic Kuramoto-Vicsek-type model for global optimization of nonconvex functions on the sphere. This model belongs to the class of …

Mar 5, 2014 · In this paper some concepts and techniques of Mathematical Programming are extended in an intrinsic way from the Euclidean space to the sphere. In particular, the notion of …

For most optimisation methods an essential assumption is the vector space structure of the feasible set. This condition is not fulfilled if we consider op-timisation problems over the …

In this paper some concepts and techniques of Mathematical Programming are extended in an intrinsic way from the Euclidean space to the sphere. In particular, the notion of convex …

Hence, we propose a Derivative-Free Geometric Algorithm (DFGA) which, to the best of our knowledge, is the rst derivative-free algorithm that takes trust region framework and explores …

Jan 1, 2019 · We cast a stochastic, hybrid algorithm for global optimization on the unit sphere in the framework of stochastic hybrid inclusions. The algorithm contains two hybrid features.

We present a uni ed treatment of the abstract problem of nding the best approx-imation between a cone and spheres in the image of a ne transformations. Prominent instances of this problem …

Abstract: This paper develops a stochastic, hybrid optimization algorithm for globally minimizing an arbitrary continuously differentiable (C 1) function on the unit sphere intersected with an …

Mar 7, 2019 · We present an algorithm for solving a special global problem over the sphere, namely the determination of Fréchet means, which are points minimising the mean distance to …

The function SphereOptimize conducts optimization on a unit sphere. If the size of neighbor near the initial value is specified, the L-BFGS-B opitmization algorithm will be called.