Academic Journal
Scalable Simulation-Optimization Method for Synthesizing Truck Tours from Trip Tables.
| Τίτλος: | Scalable Simulation-Optimization Method for Synthesizing Truck Tours from Trip Tables. |
|---|---|
| Συγγραφείς: | de Camargo, Pedro Veiga1 (AUTHOR) pveigadecamargo@anl.gov, Zuniga-Garcia, Natalia1 (AUTHOR), Stinson, Monique2 (AUTHOR) |
| Πηγή: | Procedia Computer Science. 2026, Vol. 280, p630-637. 8p. |
| Θεματικοί όροι: | Vehicle routing problem, Markov chain Monte Carlo, Freight & freightage, Computer simulation, Mathematical optimization, Automobile travel |
| Περίληψη: | Medium- and heavy-duty vehicles play a central role in freight system performance, shaping congestion, energy use, and overall network efficiency. Accurately representing truck activity in transportation models is therefore essential for evaluating strategies that strengthen freight competitiveness. Many analyses require modeling truck operations as full-day tours, yet most regional models rely on origin–destination trip tables because tour-based models are costly and data-intensive to develop. This gap limits the ability of planners to assess routing behavior, vehicle duty cycles, or technology feasibility, all of which depend on tour-level information rather than isolated trips. This paper introduces a scalable simulation–optimization method that synthesizes realistic truck tours directly from trip tables for use in large-scale agent-based simulation frameworks. Stops are generated using a Markov chain Monte Carlo process derived from trip table transition probabilities, and tour sequences are optimized through a vehicle routing formulation calibrated with publicly available vehicle miles traveled data. The method preserves the aggregate structure of the input trip tables, enabling seamless integration into existing planning workflows with minimal development effort. Case studies in two metropolitan regions demonstrate that the approach produces realistic tour patterns with acceptable computational runtimes. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: | Supplemental Index |
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