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

Ikuo Arizono; Shinji Hara; Hiroshi Ohta

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 proceeding › Conference contribution

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 language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Editors	Anon
Publisher	Publ by IEEE
Pages	1520-1523
Number of pages	4
ISBN (Print)	0780314212
Publication status	Published - Dec 1 1993
Externally published	Yes
Event	Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) - Nagoya, Jpn Duration: Oct 25 1993 → Oct 29 1993

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2

Other

Other	Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)
City	Nagoya, Jpn
Period	10/25/93 → 10/29/93

ASJC Scopus subject areas

Software
Artificial Intelligence

Fingerprint Dive into the research topics of 'Neurons with an immunological rejective function and their application to scheduling problems'. Together they form a unique fingerprint.

Cite this

Neurons with an immunological rejective function and their application to scheduling problems. / Arizono, Ikuo; Hara, Shinji; Ohta, Hiroshi.

Proceedings of the International Joint Conference on Neural Networks. ed. / Anon. Publ by IEEE, 1993. p. 1520-1523 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2).

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

Arizono, I, Hara, S & Ohta, H 1993, Neurons with an immunological rejective function and their application to scheduling problems. in Anon (ed.), Proceedings of the International Joint Conference on Neural Networks. Proceedings of the International Joint Conference on Neural Networks, vol. 2, Publ by IEEE, pp. 1520-1523, Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3), Nagoya, Jpn, 10/25/93.

@inproceedings{5e28aa0c981a49a5867dedee8a862336,

title = "Neurons with an immunological rejective function and their application to scheduling problems",

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.",

author = "Ikuo Arizono and Shinji Hara and Hiroshi Ohta",

year = "1993",

month = dec,

day = "1",

language = "English",

isbn = "0780314212",

series = "Proceedings of the International Joint Conference on Neural Networks",

publisher = "Publ by IEEE",

pages = "1520--1523",

editor = "Anon",

booktitle = "Proceedings of the International Joint Conference on Neural Networks",

note = "Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) ; Conference date: 25-10-1993 Through 29-10-1993",

}

TY - GEN

T1 - Neurons with an immunological rejective function and their application to scheduling problems

AU - Arizono, Ikuo

AU - Hara, Shinji

AU - Ohta, Hiroshi

PY - 1993/12/1

Y1 - 1993/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0027814459&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027814459&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0027814459

SN - 0780314212

T3 - Proceedings of the International Joint Conference on Neural Networks

SP - 1520

EP - 1523

BT - Proceedings of the International Joint Conference on Neural Networks

A2 - Anon, null

PB - Publ by IEEE

T2 - Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)

Y2 - 25 October 1993 through 29 October 1993

ER -

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

Abstract

Publication series

Other

ASJC Scopus subject areas

Other files and links

Cite this