Chaotic Regulation of Exploration and Exploitation in Bio-Inspired Swarm Intelligence for Combinatorial Optimization
A chaotic discretization framework is presented that replaces the classical behavior of the two-step binarization technique to regulate the balance between exploration and exploitation and shows that the highest-performing chaotic mapping is heavily influenced by the specific landscape morphology evaluated.