Distributed optimization for railway track maintenance operations planning
Muhammad Faris (Student TU Delft)
A.A. Nunez (TU Delft - Railway Engineering)
Zhou Su (TU Delft - Team Bart De Schutter)
Bart De Schutter (TU Delft - Team Bart De Schutter)
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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.