Determining optimal intervention programs for large railway infrastructure networks using a genetic algorithm
Year: 2019
Type: conference-paper
Abstract: Railway infrastructure networks deteriorate over time and interventions are required to ensure that the infrastructure provides adequate service.Optimal intervention programs for railway networks consider all objects, e.g.tracks, bridges, and switches, the dependencies between objects and between objects and the service provided, the costs related to the execution of the interventions, and the benefit achieved by executing the interventions in terms of the risk reduced by them.Although taking into consideration these things are possible for small networks using a constrained mixed integer linear network flow model and the simplex and branch and bound algorithms, [6], they are not for large networks.If the optimal intervention program cannot be found in a reasonable time in this way, it is necessary to turn to heuristics.This paper presents a problem fitted genetic algorithm to determine optimal intervention programs for large networks.The constraints are considered by the introduction of a search space transformation, correction functions, and penalty functions.The algorithm is used to determine the optimal intervention program for an example railway network.Its performance is compared to that of the simplex and branch and bound algorithm used to solve a constrained network flow problem formulation in [1].
Authors: Burkhalter, Marcel, Adey, Bryan T.
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3015048639