Analysis of an evolutionary algorithm with HyperMacromutation and stop at first constructive mutation heuristic for solving trap functions
Vincenzo Cutello, Giuseppe Nicosia, Pietro S. Oliveto · 2006
The paper presents a theoretical analysis, along with exper-imental studies, on a new evolutionary algorithm (EA) to optimize basic and complex trap functions. The designed evolutionary algorithm uses perturbation operators based on HyperMacromutation and stop at first constructive mu-tation heuristic. The experimental and theoretical results show that the algorithm successfully achieves its goal in fac-ing this computational problem. The low number of evalua-tions to solutions expected through the theoretical analysis of the EA have been fully confirmed by the experimental re-sults. To our knowledge the designed EA is the state-of-art algorithm to face trap function problems.