Abstract. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the methods of selecting inert...
—In this paper we present a multi-agent search technique to face the NP-hard single machine total weighted tardiness scheduling problem in presence of sequence-dependent setup ti...
Davide Anghinolfi, Antonio Boccalatte, Alberto Gro...
— Traditional particle swarm optimization (PSO) suffers from the premature convergence problem, which usually results in PSO being trapped in local optima. This paper presents an...
We propose a framework for optimization problems based on particle filtering (also called Sequential Monte Carlo method). This framework unifies and provides new insight into rand...
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...