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GECCO

2003

Springer

2003

Springer

Complex representation in Genetic Algorithms and pattern in real problems limits the effect of crossover to construct better pattern from sporadic building blocks. Instead of introducing more sophisticated operator, a diploid system was designed to divide the task into two steps: in meiosis phase, crossover was used to break two haploid of same individual into small units and remix them thoroughly. Then better phenotype was rebuilt from diploid of zygote in development phase. We introduced a new representation for Hamiltonian Cycle Problem and implemented an algorithm to test the system. Our algorithm is different from conventional GA in several ways: The edges of potential solution are directly represented without coding. Crossover is only part of meiosis, working between diploid of same individual. Instead of mutation, the population size guarantees the diversity of genes. Since Hamiltonian Cycle Problem is a NP-Complete problem, we can design a search algorithm for Non-dete...

Related Content

Added |
06 Jul 2010 |

Updated |
06 Jul 2010 |

Type |
Conference |

Year |
2003 |

Where |
GECCO |

Authors |
Dong Xianghui, Ruwei Dai |

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