Optimal control of large-scale batch production by evolutionary computation

Jari Hämäläinen, Olli Parviainen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    The common mathematical programming approach to the short-term scheduling and control of batch processes often leads to non-standard NP-complete mixed integer non-linear programming (MINLP) problems. It is shown that the scheduling problem can also be formulated as an optimal control problem. By the utilization of a simulation model of the process optimal operational schedules can then be found by the methods of evolutionary computation. The new approach is demonstrated by the optimization of the schedule of batches in a model of a chemical process.
    Original languageEnglish
    Title of host publicationProceedings of the 6th IFAC Symposium on Dynamics and Control of Process Systems
    EditorsGeorge Stephanopoulos, Jay Lee, En Sup Yoon
    Pages632-637
    Publication statusPublished - 2001
    MoE publication typeA4 Article in a conference publication
    Event6th IFAC Symposium on Dynamics and Control of Process Systems - Jejudo Island, Korea, Democratic People's Republic of
    Duration: 4 Jun 20016 Jun 2001

    Conference

    Conference6th IFAC Symposium on Dynamics and Control of Process Systems
    CountryKorea, Democratic People's Republic of
    CityJejudo Island
    Period4/06/016/06/01

    Keywords

    • batch control
    • genetic algorithms
    • scheduling algorithms
    • supervisory control
    • optimization
    • industrial production systems

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  • Cite this

    Hämäläinen, J., & Parviainen, O. (2001). Optimal control of large-scale batch production by evolutionary computation. In G. Stephanopoulos, J. Lee, & E. S. Yoon (Eds.), Proceedings of the 6th IFAC Symposium on Dynamics and Control of Process Systems (pp. 632-637)