In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous ...
Abstract. In this work we propose a different particle swarm optimization (PSO) algorithm that employs two key features of the conjugate gradient (CG) method. Namely, adaptive wei...
— The computation of periodic orbits of nonlinear mappings is very important for studying and better understanding the dynamics of complex systems. Evolutionary algorithms have s...
Y. G. Petalas, Konstantinos E. Parsopoulos, Michae...
This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two p...
David Ireland, Andrew Lewis, Sanaz Mostaghim, Junw...