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 …

Teaching–Learning-Based Optimization (TLBO) seems to be a rising star from amongst a
number of metaheuristics with relatively competitive performances. It is reported that it …

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\; …

This work presents a methodology for the allocation of fixed capacitor banks in electrical
power distribution systems by applying a bio-inspired optimization technique. The goal is to …

This paper presents a standardized formulation procedure for cost-safety optimization of
steel-concrete composite beam (SCCB). To this aim, the SCCB was optimized based on the …

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 …