Distributed optimization for railway track maintenance operations planning

Conference paper (2018)

Authors

AA Nunez Railway Engineering - CEG
Zhou Su Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
B De Schutter Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Department
Delft Center for Systems and Control
Copyright: © 2018 Muhammad Faris, Alfredo Nunez, Z. Su, B.H.K. De Schutter
DOI: https://doi.org/10.1109/ITSC.2018.8569335
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Published Date

2018

Language

English

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Department

Delft Center for Systems and Control

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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