Neural network approach for the real time control of a FMS

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the Hawaii International Conference on System Sciences
PublisherPubl by IEEE
Pages641-648
Volume3
ISBN (Print)818650702
StatePublished - 1994

Publication series

Name
Volume3
ISSN (Electronic)1060-3425

Conference

TitleProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5)
CityWailea, HI, USA
Period4 - 7 January 1994

Abstract

In this paper, we proposed a three phased model of the FMS control. The first phase is to identify the feasibility of job moves under given system status. The simple Sigma-Pi type of NN model has been adopted in Phase I for feasibility recognition. The second phase applies the Hopfield-Tank model to determine the most appropriate job moves from a feasible job set derived from Phase I. This problem is considered to be very difficult not only because of its NP-complete feature, but also because of the need for quick response under real-time environment. An Hopfield-Tank network with a linear energy function is proposed for Phase II. Phase III devotes to routing decisions for MHS. A heuristic algorithm based on Kohonen's Self-Organizing feature maps is proposed.

Citation Format(s)

Neural network approach for the real time control of a FMS. / Hao, Gang; Shang, Jan S.; Vargas, Luis G.

Proceedings of the Hawaii International Conference on System Sciences. Vol. 3 Publ by IEEE, 1994. p. 641-648.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review