- author = "Henri Thoelke and Jens Kosiol",
- title = "A Multiplicity-Preserving Crossover Operator on Graphs",
- booktitle = "Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings",
- year = "2022",
- pages = "588--597",
- address = "Montreal, Quebec, Canada",
- publisher = "Association for Computing Machinery",
- keywords = "genetic algorithms, genetic programming, search-based software engineering, SBSE, evolutionary algorithms, crossover, model-driven optimization, MDO, consistency-preservation",
- isbn13 = "9781450394673",
-
URL = "
https://doi.org/10.1145/3550356.3561587",
-
DOI = "
doi:10.1145/3550356.3561587",
- size = "10 pages",
- abstract = "Evolutionary algorithms usually explore a search space of solutions by means of crossover and mutation. While a mutation consists of a small, local modification of a solution, crossover mixes the genetic information of two solutions to compute a new one. For model-driven optimization (MDO), where models directly serve as possible solutions (instead of first transforming them into another representation), only recently a generic crossover operator has been developed. Using graphs as a formal foundation for models, we further refine this operator in such a way that additional well-formedness constraints are preserved: We prove that, given two models that satisfy a given set of multiplicity constraints as input, our refined crossover operator computes two new models as output that also satisfy the set of constraints.",
-
notes = "is this GP?
See https://arxiv.org/pdf/2208.10881.pdf for Extended version
Philipps-Universitaet Marburg Marburg, Germany",
