University of Sussex
Browse

File(s) not publicly available

Application of Stochastic Real-Valued Reinforcement Neural Networks to Batch Production Rescheduling

journal contribution
posted on 2023-06-08, 08:36 authored by M I Heywood, M C Chan, Chris ChatwinChris Chatwin
This paper details the design and application of a hybrid neural network architecture for the rescheduling problem of batch manufacture. Design issues include the selection of an appropriate neural network paradigm, specification of the network architecture and support for multistep prediction. Application issues include decoupling the network dimension from that of the problem and the definition of suitable rescheduling operators. The ensuing hybrid network is tested against heuristics previously identified as typically representing estimates for best and worst case performance within a cross-section of batch rescheduling problems.

History

Publication status

  • Published

Journal

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

ISSN

0954-4054

Publisher

Professional Engineering Publishing

Issue

B

Volume

211

Page range

591-603

ISBN

0954-4054

Department affiliated with

  • Engineering and Design Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC