A Genetic Algorithm Based on Stochastic Crossover for DHCP

Author

Carpentieri, Marco

Author_Institution

Dipt. di Fisica E. R. Caianiello, Universita degli Studi di Salerno

fYear

2007

fDate

1-5 April 2007

Firstpage

259

Lastpage

266

Abstract

We introduce a genetic model based on stochastic crossover to solve the Hamiltonian cycle problem (DHCP) for random digraphs containing a random Hamiltonian cycle. The genetic model represents a new decision computational method inspired by the remark that DHCP can be formulated as determining the compatibility of a quadratic system over the finite field GF(2). A (simple) genetic algorithm based on the stochastic crossover is experimentally compared with a randomized algorithm based on the Angulin and Valiant classic technique designed to find Hamiltonian cycles in random digraphs

Keywords

Galois fields; genetic algorithms; graph theory; random processes; stochastic processes; Galois field; Hamiltonian cycle problem; decision computation; genetic algorithm; quadratic system; random Hamiltonian cycle; random digraphs; randomized algorithm; stochastic crossover; Adaptive control; Algorithm design and analysis; Application specific integrated circuits; Biological cells; Computational intelligence; Design optimization; Galois fields; Genetic algorithms; Merging; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Foundations of Computational Intelligence, 2007. FOCI 2007. IEEE Symposium on

Conference_Location

Honolulu, HI

Print_ISBN

1-4244-0703-6

Type

conf

DOI

10.1109/FOCI.2007.372178

Filename

4233916