Simplicial decomposition of variational inequalities with multiple nonlinear column generation

William Chung*

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    25 Downloads (CityUHK Scholars)

    Abstract

    Simplicial decomposition (SD) of variational inequalities experiences the long-tail convergence property. That is, the equilibrium solution rapidly progresses at first but then tails off, making only a tiny amount of progress per column generation iteration, which is a drawback of SD-VI. In the context of Dantzig-Wolfe of LP, it is reported that the more proposals are used to initialize the algorithm, the faster the solution can be found by reducing the number of decomposition steps. Therefore, I proposed to solve multiple nonlinear column generation (mNCG) subproblems in each SD-VI iteration (SD-VI-mNCG) instead of solving only one subproblem as in SD-VI. Generating multiple column generation subproblem solutions in each SD-VI iteration enabled the corresponding convex hull to be rapidly enlarged. Consequently, the number of SD-VI iterations could be greatly reduced. A transportation network equilibrium problem was used to study the performance of the SD-VI-mNCG. © 2024 the Author(s), licensee AIMS Press.
    Original languageEnglish
    Pages (from-to)14618-14639
    JournalAIMS Mathematics
    Volume9
    Issue number6
    Online published23 Apr 2024
    DOIs
    Publication statusPublished - 2024

    Funding

    Financial support for William Chung’s work came from the Research Grants Council of Hong Kong S.A.R., China (CityU 11500022).

    Research Keywords

    • column generation
    • convergence rate
    • nonlinear programming
    • simplicial decomposition
    • variational inequalities

    Publisher's Copyright Statement

    • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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