2 research outputs found
On the Velocity Update in Multi-Objective Particle Swarm Optimizers
Since its appearance, Particle Swarm Optimization (PSO) has become a very
popular technique for solving optimization problems because of both its simplicity and its fast
convergence properties. In the last few years there has been a variety of proposals for
extending it to handle with multiples objectives. Although many of them keep the same properties
of the original algorithm, they face difficulties when tackling the optimization of some
multi-modal problems, i.e., those having more than one suboptimal front of solutions. Recent
studies have shown that this disadvantage could be related to the velocity of the particles:
uncontrolled high velocities may have no effect in particles movements. While many of the
contributions on the specialized literature have focused on the selection of the leaders of the
swarm, studies about different schemes for controlling the velocity of the particles are scarce
in the multi-objective domain. In this work, we study different mechanisms in order to
update the velocity of each particle with the idea of enhancing the search capabilities of
multi-objective PSO algorithms. Our experiments show that some modifications help to
over-coming the difficulties observed in previous proposals when dealing with hard
optimization problems.Ministerio de Ciencia e Innovaci贸n TIN2008-06491-C04-01Junta de Andaluc铆a P07-TIC-03044Ministerio de Ciencia e Innovaci贸n BES-2009-01876