Linkage tree genetic algorithms: variants and analysis

@inproceedings{Goldman2012LinkageTG,
  title={Linkage tree genetic algorithms: variants and analysis},
  author={Brian W. Goldman and Daniel R. Tauritz},
  booktitle={GECCO},
  year={2012}
}
Discovering and exploiting the linkage between genes during evolutionary search allows the Linkage Tree Genetic Algorithm (LTGA) to maximize crossover effectiveness, greatly reducing both population size and total number of evaluations required to reach success on decomposable problems. This paper presents a comparative analysis of the most prominent LTGA variants and a newly introduced variant. While the deceptive trap problem (Trap-k) is one of the canonical benchmarks for testing LTGA, when… CONTINUE READING