Scheduled Service Network Design supports consolidation-based freight carriers in setting up a transportation network by selecting the transportation services to operate, with their schedules, and the itineraries of the commodities to move. We propose a new formulation to the problem that represents time in its continuous nature, directly over the physical graph, thus mitigating the drawbacks that a traditional formulation, relying on a time-space network, may have for large-scale instances, due to the increase in its dimensions and the consequent intractability in solving the problem exactly. Preliminary numerical experiments comparing the new and traditional formulations on a set of randomly generated instances are performed. Results highlight that the proposed formulation is a valuable tool to solve large-scale instances with a long schedule length.
Lanza, G., Crainic, T., Passacantando, M., Scutellà, M. (2024). A Continuous Time Physical Graph based Formulation to Scheduled Service Network Design. In M. Bruglieri, P. Festa, G. Macrina, O. Pisacane (a cura di), Optimization in Green Sustainability and Ecological Transition ODS, Ischia, Italy, September 4–7, 2023 Conference proceedings (pp. 265-275). Cham : Springer [10.1007/978-3-031-47686-0_24].
A Continuous Time Physical Graph based Formulation to Scheduled Service Network Design
Passacantando, M;
2024
Abstract
Scheduled Service Network Design supports consolidation-based freight carriers in setting up a transportation network by selecting the transportation services to operate, with their schedules, and the itineraries of the commodities to move. We propose a new formulation to the problem that represents time in its continuous nature, directly over the physical graph, thus mitigating the drawbacks that a traditional formulation, relying on a time-space network, may have for large-scale instances, due to the increase in its dimensions and the consequent intractability in solving the problem exactly. Preliminary numerical experiments comparing the new and traditional formulations on a set of randomly generated instances are performed. Results highlight that the proposed formulation is a valuable tool to solve large-scale instances with a long schedule length.File | Dimensione | Formato | |
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