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Portfolio Design and Pricing for Multimodal Mobility-on-Demand Services Considering Traveler Responses — arXiv:2610.07590

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.07590
License (as archived): CC0-1.0
Archived: 2026-10-07T21:07:13.292Z
SHA-256 of the archived text: 59016a66196bd5753a2e83f6114c267e639dd5a893b9c7e1630c70cb98b08bb9
Stable URL of this page: https://metraipolis.com/documento/dc_e586cdcd8a6a

How to cite

Portfolio Design and Pricing for Multimodal Mobility-on-Demand Services Considering Traveler Responses — arXiv:2610.07590 — arXiv (en), https://arxiv.org/abs/2610.07590 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e586cdcd8a6a (Metraipolis archive dc_e586cdcd8a6a, sha256 59016a66196bd5753a2e83f6114c267e639dd5a893b9c7e1630c70cb98b08bb9)

BibTeX

@misc{dce586cdcd8a6a,
  title = {Portfolio Design and Pricing for Multimodal Mobility-on-Demand Services Considering Traveler Responses — arXiv:2610.07590},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.07590},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e586cdcd8a6a; sha256 59016a66196bd5753a2e83f6114c267e639dd5a893b9c7e1630c70cb98b08bb9},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.07590. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Mobility-on-demand (MoD) platforms can offer exclusive, pooled, and transit-connected services to accommodate different passenger needs. However, determining which services to offer and at what prices is challenging because profitability depends on both passenger choices and operational feasibility. This paper proposes a real-time framework that jointly optimizes service menus, fares, and vehicle trip plans for individual MoD requests. Passenger choices are modeled using a generalized nested logit (GNL) model that captures correlated substitution among service options based on vehicle sharing and transit use. To solve the resulting nonlinear fare-optimization problem, we use Fenchel duality to transform the nonlinear objective from the fare domain to the choice-probability domain, yielding a concave maximization involving a generalized entropy term. We evaluate the framework through operational simulations using real-world New York City trip records. Joint portfolio design and pricing improve operator service margins by 28.4% and 8.5% compared with optimizing only service menus and only fares, respectively. Furthermore, the proposed reformulation is up to 18.8 times faster than solving the original pricing problem directly in fare space, improving computational efficiency for real-time MoD operations.

Tema degli esploratori: calcolo e infrastrutture (elenco arXiv eess.SY, nuovi lavori del giorno).
Categorie arXiv: Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2610.07590 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T20:38:49.037Z dalla pagina https://arxiv.org/list/eess.SY/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).