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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 language | English |
|---|---|
| Pages (from-to) | 14618-14639 |
| Journal | AIMS Mathematics |
| Volume | 9 |
| Issue number | 6 |
| Online published | 23 Apr 2024 |
| DOIs | |
| Publication status | Published - 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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GRF: Multiple Column Generation Algorithms for Variational Inequalities
CHUNG, S. W. W. (Principal Investigator / Project Coordinator)
1/01/23 → …
Project: Research