Reference
M. Faris, A. Núñez, Z. Su, and B. De Schutter, "Distributed
optimization for railway track maintenance operations planning,"
Proceedings of the 2018 21st International Conference on Intelligent
Transportation Systems (ITSC), Maui, Hawaii, pp. 1194-1201, Nov. 2018.
Abstract
In this paper, distributed optimization approaches are developed for the
planning of maintenance operations of large-scale railway infrastructure
formulated as a Mixed-Integer Linear Programming (MILP) problem. The proposed
planning problem is solved using three different distributed optimization
schemes: Parallel Augmented Lagrangian Relaxation (PALR), Alternating Direction
Method of Multipliers (ADMM), and Distributed Robust Safe But Knowledgeable
(DRSBK). The original distributed algorithms are modified to handle the
non-convex nature of the optimization problem and to improve the solution
quality. The results of large-scale test instances show that DRSBK can
outperform the other distributed approaches, by providing the
closest-to-optimum solution while requiring the lowest computation time.
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BibTeX
@inproceedings{FarNun:18-027,
author = {Faris, Muhammad and N{\'{u}}{\~{n}}ez, Alfredo and Su, Zhou and
De Schutter, Bart},
title = {Distributed Optimization for Railway Track Maintenance
Operations Planning},
booktitle = {Proceedings of the 2018 21st International Conference on
Intelligent Transportation Systems (ITSC)},
address = {Maui, Hawaii},
pages = {1194--1201},
month = nov,
year = {2018}
}