Genetic Operators for Permutation Representation
The permutation representation for genetic algorithms requires specialized operators. A wide variety of crossover and mutation operators for permutations exist in the research literature. In my research on evolutionary computation for optimizing permutation structures, I have developed several crossover and mutation operators, including Cycle Mutation, Non-Wrapping Order Crossover (NWOX), Uniform Partially Matched Crossover (UPMX), Heuristic Sequencing Crossover (HeurX), and window-limited variations of common permutation mutation operators.
Selected Publications
- A Survey and Analysis of Evolutionary Operators for Permutations.
Vincent A. Cicirello.
In Proceedings of the 15th International Joint Conference on Computational Intelligence, pages 288-299. November 2023. doi:10.5220/0012204900003595
[PDF] [BIB] [DOI] [arXiv] [CODE] - On Fitness Landscape Analysis of Permutation Problems: From Distance Metrics to Mutation Operator Selection.
Vincent A. Cicirello.
Mobile Networks and Applications, 28(2): 507-517, April 2023. doi:10.1007/s11036-022-02060-z
[PDF] [BIB] [DOI] [PUB] [arXiv] [CODE] - Cycle Mutation: Evolving Permutations via Cycle Induction.
Vincent A. Cicirello.
Applied Sciences, 12(11), Article 5506, June 2022. doi:10.3390/app12115506
[PDF] [BIB] [DOI] [arXiv] [CODE] - On the Effects of Window-Limits on the Distance Profiles of Permutation Neighborhood Operators.
Vincent A. Cicirello.
In Proceedings of the 8th International Conference on Bio-inspired Information and Communications Technologies, pages 28-35. EAI, December 2014.
[PDF] [BIB] [PUB] - Heuristic Sequencing Crossover: Integrating Problem Dependent Heuristic Knowledge into a Genetic Algorithm.
Vincent A. Cicirello.
In Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, FLAIRS-23, pages 14-19. AAAI Press, May 2010.
[PDF] [BIB] [PUB] - Non-Wrapping Order Crossover: An Order Preserving Crossover Operator that Respects Absolute Position.
Vincent A. Cicirello.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), volume 2, pages 1125-1131. ACM Press, July 2006. doi:10.1145/1143997.1144177
Nominated for the Genetic Algorithms Track Best Paper Award.
[PDF] [BIB] [DOI] [PUB] - Modeling GA Performance for Control Parameter Optimization.
Vincent A. Cicirello and Stephen F. Smith.
In GECCO-2000: Proceedings of the Genetic and Evolutionary Computation Conference, pages 235-242. Morgan Kaufmann Publishers, July 2000.
[PDF] [BIB] [PUB]