Particle swarm optimization (PSO) is characterized by a fast convergence, which can lead
the algorithms of this class to stagnate in local optima. In this paper, a variant of the standard …

PSO-2S is a multi-swarm PSO algorithm using charged particles in a partitioned search
space for continuous optimization problems. This algorithm uses two kinds of swarms, a main …

This paper details the Multiobjective Differential Evolution algorithm (MODE) using crowding
distance for the sizing of analog circuits. MODE is used to compute the Pareto front of a …

This paper proposes an enhanced variant of the particle swarm optimization technique PSO-2S,
and its application to analogue circuit performance optimization. For comparison …

Particle swarm optimization is an optimization method based on a simulated social behavior
displayed by artificial particles in a swarm, inspired from bird flocks and fish schools. An …

In image processing, finding the optimal threshold(s) for an image with a multimodal histogram
can be done by solving a Gaussian curve fitting problem, ie fitting a sum of Gaussian …

OBJECTIVES Our goal was to analyse adverse events in adolescent and adult patients with
the Berlin Heart EXCOR and to assess the outcome of a subsequent heart transplant (HTX). …

Simple Summary Our study shows that the Berlin Heart ® EXCOR as a biventricular assist
device in adult patients is an effective strategy in heart failure medicine. Our results may …

La résolution satisfaisante d'un problème d'optimisation difficile, qui comporte un grand nombre
de solutions sous-optimales, justifie souvent le recours à une métaheuristique puissante…

Purpose Giant paraesophageal hernia (GPEH) is a challenging problem for surgeons because
of its high recurrence rate. This study was conducted to compare the outcomes in type IV …