Euclidean distance geometry is the study of Euclidean geometry based on the concept of
distance. This is useful in several applications where the input data consist of an incomplete …

The Molecular Distance Geometry Problem (MDGP) consists in finding an embedding in R3
of a nonnegatively weighted simple undirected graph with the property that the Euclidean …

Data Mining in Agriculture represents a comprehensive effort to provide graduate students
and researchers with an analytical text on data mining techniques applied to agriculture and …

Given a simple weighted undirected graph G=(V, E, d) with d: E→ ℝ+, the Molecular
Distance Geometry Problem (MDGP) consists in finding an embedding x: V→ ℝ 3 such …

Distance geometry problems (DGP) arise from the need to position entities in the Euclidean
K‐space given some of their respective distances. Entities may be atoms (molecular …

Abstract The Distance Geometry Problem in three dimensions consists in finding an
embedding in R^ 3 of a given nonnegatively weighted simple undirected graph such that …

We introduce the discretizable distance geometry problem in R^ 3 (DDGP 3), which consists
in a subclass of instances of the Distance Geometry Problem for which an embedding in R …

Given a weighted, undirected simple graph G=(V, E, d)(where d: E → R _+), the distance
geometry problem (DGP) is to determine an embedding x: V → R^ K such that ∀ {i, j\} ∈ E\; …

The best known method to find exact or at least ε-approximate solutions to polynomial-
programming problems is the spatial Branch-and-Bound algorithm, which rests on …

We present MD-jeep, an implementation of a Branch & Prune (BP) algorithm, which we
employ for the solution of distance geometry problems related to molecular conformations …