Analysis of an evolutionary algorithm with HyperMacromutation and stop at first constructive mutation heuristic for solving trap functions

Authors:
V. Cutello;G. Nicosia;P. S. Oliveto
Affiliations:
University of Catania, V.le A. Doria;University of Catania, V.le A. Doria;University of Catania, V.le A. Doria
Venue:
Proceedings of the 2006 ACM symposium on Applied computing
Year:
2006

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Abstract

The paper presents a theoretical analysis, along with experimental 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 mutation heuristic. The experimental and theoretical results show that the algorithm successfully achieves its goal in facing this computational problem. The low number of evaluations to solutions expected through the theoretical analysis of the EA have been fully confirmed by the experimental results. To our knowledge the designed EA is the state-of-art algorithm to face trap function problems.