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Optimizing Multi-Tier Intermediation in Programmatic Advertising: A DAG-Based Mechanism for Supply Path Optimization — arXiv:2611.11651

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.11651
License (as archived): CC0-1.0
Archived: 2026-11-10T18:41:27.479Z
SHA-256 of the archived text: d369329de9f8693c92d6b31986b6daa312d3458acd1d118965a3293d602f504e
Stable URL of this page: https://metraipolis.com/documento/dc_61dc3ec2cd30

How to cite

Optimizing Multi-Tier Intermediation in Programmatic Advertising: A DAG-Based Mechanism for Supply Path Optimization — arXiv:2611.11651 — arXiv (en), https://arxiv.org/abs/2611.11651 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_61dc3ec2cd30 (Metraipolis archive dc_61dc3ec2cd30, sha256 d369329de9f8693c92d6b31986b6daa312d3458acd1d118965a3293d602f504e)

BibTeX

@misc{dc61dc3ec2cd30,
  title = {Optimizing Multi-Tier Intermediation in Programmatic Advertising: A DAG-Based Mechanism for Supply Path Optimization — arXiv:2611.11651},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.11651},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_61dc3ec2cd30; sha256 d369329de9f8693c92d6b31986b6daa312d3458acd1d118965a3293d602f504e},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.11651. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Digital programmatic advertising operates through complex, multi-hop supply chains. The opacity of these intermediary networks leads to significant efficiency losses, often referred to as the ``ad-tech tax.'' While current industry practices utilize heuristic Supply Path Optimization (SPO) to trim inefficient routes, they fail to optimize the equilibrium of the entire network. This paper extends previous work on Directed Acyclic Graph (DAG) intermediation models by applying them to traceable programmatic supply chains mapped via the OpenRTB SupplyChain object. We introduce multi-attribute utility functions and Mixed-Integer Linear Programming (MILP) to account for substitutable routing (OR nodes) and percentage-based fee structures. Furthermore, we outline a computational methodology and experimental framework using public \texttt{schain} and \texttt{ this http URL } data to benchmark optimal Nash social welfare against current uncoordinated market outcomes.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2611.11651 — 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 2026-11-10T18:37:37.517Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).