### Abstract

Two improved neural algorithms are presented for solving a placement problem which is a familiar class of NP-hard quadratic assignment problems. Formulation of the problem as a zero-one integer programming leads to an improved form of the Hopfield networks, while a mixed integer programming formulation results in an analogue algorithm similar to the elastic nets. The outermost loop in these algorithms performs an automatically scheduled deterministic annealing. This gives us a natural interpretation of the annealing procedure derived straightforwardly from the mathematical programming framework. Experiments reveal that the adaptive elastic net algorithm outperforms the adaptive Hopfield method.

Original language | English |
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Title of host publication | Proceedings of the International Joint Conference on Neural Networks |

Publisher | Publ by IEEE |

Pages | 2421-2424 |

Number of pages | 4 |

Volume | 3 |

ISBN (Print) | 0780314212, 9780780314214 |

Publication status | Published - 1993 |

Externally published | Yes |

Event | Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn Duration: Oct 25 1993 → Oct 29 1993 |

### Other

Other | Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) |
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City | Nagoya, Jpn |

Period | 10/25/93 → 10/29/93 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Engineering(all)

### Cite this

*Proceedings of the International Joint Conference on Neural Networks*(Vol. 3, pp. 2421-2424). Publ by IEEE.

**Neural algorithms for placement problems.** / Urahama, Kiichi; Nishiyuki, Hiroshi.

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

*Proceedings of the International Joint Conference on Neural Networks.*vol. 3, Publ by IEEE, pp. 2421-2424, Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3), Nagoya, Jpn, 10/25/93.

}

TY - GEN

T1 - Neural algorithms for placement problems

AU - Urahama, Kiichi

AU - Nishiyuki, Hiroshi

PY - 1993

Y1 - 1993

N2 - Two improved neural algorithms are presented for solving a placement problem which is a familiar class of NP-hard quadratic assignment problems. Formulation of the problem as a zero-one integer programming leads to an improved form of the Hopfield networks, while a mixed integer programming formulation results in an analogue algorithm similar to the elastic nets. The outermost loop in these algorithms performs an automatically scheduled deterministic annealing. This gives us a natural interpretation of the annealing procedure derived straightforwardly from the mathematical programming framework. Experiments reveal that the adaptive elastic net algorithm outperforms the adaptive Hopfield method.

AB - Two improved neural algorithms are presented for solving a placement problem which is a familiar class of NP-hard quadratic assignment problems. Formulation of the problem as a zero-one integer programming leads to an improved form of the Hopfield networks, while a mixed integer programming formulation results in an analogue algorithm similar to the elastic nets. The outermost loop in these algorithms performs an automatically scheduled deterministic annealing. This gives us a natural interpretation of the annealing procedure derived straightforwardly from the mathematical programming framework. Experiments reveal that the adaptive elastic net algorithm outperforms the adaptive Hopfield method.

UR - http://www.scopus.com/inward/record.url?scp=0027836014&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027836014&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0027836014

SN - 0780314212

SN - 9780780314214

VL - 3

SP - 2421

EP - 2424

BT - Proceedings of the International Joint Conference on Neural Networks

PB - Publ by IEEE

ER -