Heterosis-Based Crossover: Leveraging Structural Differences to Control Diversity and Bloat in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8528

@InProceedings{lillo:2025:GECCOcomp,

• author = "Lute Lillo and Nick Cheney",
• title = "Heterosis-Based Crossover: Leveraging Structural Differences to Control Diversity and Bloat in Genetic Programming",
• booktitle = "Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion",
• year = "2025",
• editor = "Aniko Ekart and Nelishia Pillay",
• pages = "631--634",
• address = "Malaga, Spain",
• series = "GECCO '25 Companion",
• month = "14-18 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, diversity, symbolic regression, bloat, introns, heterosis crossover, inbreeding",
• isbn13 = "979-8-4007-1464-1",
• URL = "https://doi.org/10.1145/3712255.3734582",
• DOI = "doi:10.1145/3712255.3734582",
• size = "4 pages",
• abstract = "Genetic programming (GP) is an evolutionary approach to the automated synthesis of computer programs. A critical challenge in GP is balancing population diversity and efficiency to prevent premature convergence while avoiding excessive program growth, commonly referred to as bloat. This work introduces a new syntactic-based crossover mechanism, Heterosis-based Crossover (HBC), which prioritizes structural differences over semantic criteria. Specifically, HBC enforces mating constraints by employing a structural diversity metric that restricts mating between individuals deemed too similar, effectively preventing {"}inbreeding.{"} Through a series of symbolic regression tasks, we investigate how HBC influences population diversity, introns (structurally non-effective code), and bloat. Our findings reveal that HBC reduces premature convergence, preserves diversity, and mitigates bloat, enabling more effective exploration of the solution space. This study demonstrates that syntactic-based techniques offer a robust alternative to semantic-aware methods, emphasizing the importance of structural diversity in optimizing the trade-offs among exploration, exploitation, and computational resources in GP.",
• notes = "GECCO-2025 GP A Recombination of the 34th International Conference on Genetic Algorithms (ICGA) and the 30th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Lute Lillo Nick Cheney

Citations