Neurons with an immunological rejective function and their application to scheduling problems

Ikuo Arizono, Shinji Hara, Hiroshi Ohta

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

1 Citation (Scopus)

Abstract

If the energy function of an artificial neural network system is expressed in quadratic form based on the objective function and constraints of a combinatorial optimization problem, it is possible to get a solution using the equations of system dynamics; a special algorithm is not required. However, even though the subenergy functions based on the constraints can be expressed in quadratic form, minimizing the subenergy functions does not necessarily give a feasible solution satisfying the constraints of the optimization problem. This shows that neural network systems have a limit in their applicability. In this paper we propose new neurons, with an immunological rejective function, so as to extend the applicability of neural network system. These neurons have the function of rejecting the violation of constraints. We apply these neurons to scheduling problems and discuss their capabilities.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages1520-1523
Number of pages4
ISBN (Print)0780314212
Publication statusPublished - Dec 1 1993
Externally publishedYes
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) - Nagoya, Jpn
Duration: Oct 25 1993Oct 29 1993

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)
CityNagoya, Jpn
Period10/25/9310/29/93

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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