### Abstract

Characterization of trajectory structure of fitness landscapes is a major problem of evolutionary computation theory. In this paper a hardness measure of fitness landscapes is introduced which is based on statistical properties of trajectories. These properties are approximated with the help of a heuristic based on the transition probabilities between the elements of the search space. This makes it possible to compute the measure for some well-known functions: a ridge function, a long path function, a fully deceptive function and a combinatorial problem: the subset sum problem. Using the same transition probabilities the expected number of evaluations needed to reach the global optimum from any point in the space are approximated and examined for the above problems.

Original language | English |
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Title of host publication | Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999 |

Publisher | IEEE Computer Society |

Pages | 623-630 |

Number of pages | 8 |

Volume | 1 |

DOIs | |

Publication status | Published - 1999 |

Event | 1999 Congress on Evolutionary Computation, CEC 1999 - Washington, DC, United States Duration: Jul 6 1999 → Jul 9 1999 |

### Other

Other | 1999 Congress on Evolutionary Computation, CEC 1999 |
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Country | United States |

City | Washington, DC |

Period | 7/6/99 → 7/9/99 |

### Fingerprint

### ASJC Scopus subject areas

- Computational Mathematics

### Cite this

*Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999*(Vol. 1, pp. 623-630). [781990] IEEE Computer Society. https://doi.org/10.1109/CEC.1999.781990

**Characterizations of trajectory structure of fitness landscapes based on pairwise transition probabilities of solutions.** / Jelasity, M.; Toth, Boglarka; Vinko, Tamas.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999.*vol. 1, 781990, IEEE Computer Society, pp. 623-630, 1999 Congress on Evolutionary Computation, CEC 1999, Washington, DC, United States, 7/6/99. https://doi.org/10.1109/CEC.1999.781990

}

TY - GEN

T1 - Characterizations of trajectory structure of fitness landscapes based on pairwise transition probabilities of solutions

AU - Jelasity, M.

AU - Toth, Boglarka

AU - Vinko, Tamas

PY - 1999

Y1 - 1999

N2 - Characterization of trajectory structure of fitness landscapes is a major problem of evolutionary computation theory. In this paper a hardness measure of fitness landscapes is introduced which is based on statistical properties of trajectories. These properties are approximated with the help of a heuristic based on the transition probabilities between the elements of the search space. This makes it possible to compute the measure for some well-known functions: a ridge function, a long path function, a fully deceptive function and a combinatorial problem: the subset sum problem. Using the same transition probabilities the expected number of evaluations needed to reach the global optimum from any point in the space are approximated and examined for the above problems.

AB - Characterization of trajectory structure of fitness landscapes is a major problem of evolutionary computation theory. In this paper a hardness measure of fitness landscapes is introduced which is based on statistical properties of trajectories. These properties are approximated with the help of a heuristic based on the transition probabilities between the elements of the search space. This makes it possible to compute the measure for some well-known functions: a ridge function, a long path function, a fully deceptive function and a combinatorial problem: the subset sum problem. Using the same transition probabilities the expected number of evaluations needed to reach the global optimum from any point in the space are approximated and examined for the above problems.

UR - http://www.scopus.com/inward/record.url?scp=84878267031&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84878267031&partnerID=8YFLogxK

U2 - 10.1109/CEC.1999.781990

DO - 10.1109/CEC.1999.781990

M3 - Conference contribution

AN - SCOPUS:84878267031

VL - 1

SP - 623

EP - 630

BT - Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999

PB - IEEE Computer Society

ER -