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[Submitted on 11 Oct 2024 (v1), last revised 24 Aug 2026 (this version, v4)]
Abstract:Designing a network (e.g., a telecommunication or transport network) is mainly done offline, in a planning phase, prior to the operation of the network. On the other hand, a massive effort has been devoted to characterizing dynamic networks, i.e., those that evolve over time. The novelty of this paper is that we introduce a method for the online design of dynamic networks. The need to do so emerges when a network needs to operate in a dynamic and stochastic environment. In this case, one may wish to build a network over time, on the fly, in order to react to the changes of the environment and to keep certain performance targets. We tackle this online design problem with a rolling horizon optimization based on Monte Carlo Tree Search. The potential of online network design is showcased for the design of a futuristic dynamic public transport network, where bus lines are constructed on the fly to better adapt to a stochastic user demand. In such a scenario, we compare our results with state-of-the-art dynamic vehicle routing problem (VRP) resolution methods, simulating requests from a New York City taxi dataset. Differently from classic VRP methods, that extend vehicle trajectories in isolation, our method enables us to build a structured network of line buses, where complex user journeys are possible, thus increasing system performance.
Submission history
From: Andrea Araldo [view email]
[v1]
Fri, 11 Oct 2024 14:50:31 UTC (4,943 KB)
[v2]
Mon, 30 Mar 2026 22:39:25 UTC (2,716 KB)
[v3]
Fri, 21 Aug 2026 17:07:40 UTC (2,716 KB)
[v4]
Mon, 24 Aug 2026 08:08:21 UTC (2,716 KB)
추출 본문 · 출처: arxiv.org · https://arxiv.org/abs/2410.08875