Neural algorithms for placement problems

Kiichi Urahama, Hiroshi Nishiyuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherPubl by IEEE
Pages2421-2424
Number of pages4
Volume3
ISBN (Print)0780314212, 9780780314214
Publication statusPublished - 1993
Externally publishedYes
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
Duration: Oct 25 1993Oct 29 1993

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period10/25/9310/29/93

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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