Particle swarm optimization method in multiobjective problems

KE Parsopoulos, MN Vrahatis - … of the 2002 ACM symposium on Applied …, 2002 - dl.acm.org
This paper constitutes a first study of the Particle Swarm Optimization (PSO) method in
Multiobjective Optimization (MO) problems. The ability of PSO to detect Pareto Optimal …

On the computation of all global minimizers through particle swarm optimization

KE Parsopoulos, MN Vrahatis - IEEE Transactions on …, 2004 - ieeexplore.ieee.org
This paper presents approaches for effectively computing all global minimizers of an
objective function. The approaches include transformations of the objective function through …

Opposition-based particle swarm algorithm with Cauchy mutation

H Wang, H Li, Y Liu, C Li, S Zeng - 2007 IEEE congress on …, 2007 - ieeexplore.ieee.org
Particle swarm optimization (PSO) has shown its fast search speed in many complicated
optimization and search problems. However, PSO could often easily fall into local optima …

Particle swarm optimization for integer programming

EC Laskari, KE Parsopoulos… - Proceedings of the 2002 …, 2002 - ieeexplore.ieee.org
The investigation of the performance of the particle swarm optimization (PSO) method in
integer programming problems, is the main theme of the present paper. Three variants of …

A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques

L Zhang, Y Tang, C Hua, X Guan - Applied Soft Computing, 2015 - Elsevier
Particle swarm optimization is a stochastic population-based algorithm based on social
interaction of bird flocking or fish schooling. In this paper, a new adaptive inertia weight …