This paper addresses the complex iterative process railway managers currently use to sequence necessary interventions 2-10 years in advance, which requires extensive knowledge of costs, service impacts, locations, and failure risks. The authors propose a mixed integer linear programming algorithm that optimizes multicomponent railway intervention programs by maximizing net benefit while considering possession windows, costs, service impacts, and interdependencies, demonstrating up to 58% improvement in net benefit when tested on a 25-km Swiss railway network.
Hamed Mehranfar,
Bryan T Adey,
Saviz Moghtadernejad,
Claudia Fecarotti
