The paper provides an insight into the improved novel meta- heuristics of the Fire°y Algorithm for constrained continuous optimiza- tion tasks. The presented technique is inspired by social behavior of ¯re- °ies and the phenomenon of bioluminescent communication. The ¯rst part of the paper is devoted to the detailed description of the existing al- gorithm. Then some suggestions for extending the simple scheme of the technique under consideration are presented. Subsequent sections con- centrate on the performed experimental parameter studies and a com- parison with existing Particle Swarm Optimization strategy based on existing benchmark instances. Finally some concluding remarks on pos- sible algorithm extensions are given, as well as some properties of the presented approach and comments on its performance in the constrained continuous optimization tasks.