Near optimal jobshop scheduling using neural network parallel computing

Akira Hanada, Kouhei Ohnishi

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

9 Citations (Scopus)

Abstract

A parallel algorithm based on the neural network model for jobshop scheduling problem is presented in this paper. In the manufacturing system, it is becoming more complex to manage operations of facilities, because of many requirements and constraints such as to increase product throughput, reduce work-in-process and keep the due date. The goal of the proposed parallel algorithm is to find a near-optimum scheduling solution for the given schedule. The proposed parallel algorithm requires N × N processing elements (neurons) where N is the number of operations. Our empirical study on the sequential shows the behavior of the system.

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Editors Anon
PublisherPubl by IEEE
Pages315-320
Number of pages6
Volume1
ISBN (Print)0780308913
Publication statusPublished - 1993
EventProceedings of the 19th International Conference on Industrial Electronics, Control and Instrumentation - Maui, Hawaii, USA
Duration: 1993 Nov 151993 Nov 18

Other

OtherProceedings of the 19th International Conference on Industrial Electronics, Control and Instrumentation
CityMaui, Hawaii, USA
Period93/11/1593/11/18

Fingerprint

Parallel processing systems
Parallel algorithms
Scheduling
Neural networks
Neurons
Throughput
Processing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Hanada, A., & Ohnishi, K. (1993). Near optimal jobshop scheduling using neural network parallel computing. In Anon (Ed.), IECON Proceedings (Industrial Electronics Conference) (Vol. 1, pp. 315-320). Publ by IEEE.

Near optimal jobshop scheduling using neural network parallel computing. / Hanada, Akira; Ohnishi, Kouhei.

IECON Proceedings (Industrial Electronics Conference). ed. / Anon. Vol. 1 Publ by IEEE, 1993. p. 315-320.

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

Hanada, A & Ohnishi, K 1993, Near optimal jobshop scheduling using neural network parallel computing. in Anon (ed.), IECON Proceedings (Industrial Electronics Conference). vol. 1, Publ by IEEE, pp. 315-320, Proceedings of the 19th International Conference on Industrial Electronics, Control and Instrumentation, Maui, Hawaii, USA, 93/11/15.
Hanada A, Ohnishi K. Near optimal jobshop scheduling using neural network parallel computing. In Anon, editor, IECON Proceedings (Industrial Electronics Conference). Vol. 1. Publ by IEEE. 1993. p. 315-320
Hanada, Akira ; Ohnishi, Kouhei. / Near optimal jobshop scheduling using neural network parallel computing. IECON Proceedings (Industrial Electronics Conference). editor / Anon. Vol. 1 Publ by IEEE, 1993. pp. 315-320
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