Dynamically tuning the population size in particle swarm optimization
Proceedings of the 2008 ACM symposium on Applied computing
| Hi-index | 0.00 |
Considering the population size is a critical parameter to define in evolutionary computation, in this paper an improved parallel evolutionary algorithm that incorporates different mechanisms to adapt the population size to the current status, is presented. Those mechanisms are based on Resizing on Fitness Improvement GA (PRoFIGA) and Variable Population Size (GAVaPS). Results indicate these incorporations are a reasonable choice when refinement in solutions is necessary.