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DOI: 10.4230/OASIcs.ATMOS.2026.15

Large Scale Middle Mile Network Design Through Efficient Local Search

Authors: Carlo S. Sartori, Jian Shen, Anastasia Kireeva, Mattia Neroni, and Philipp Loick

Published in: OASIcs, Volume 147, 26th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2026)

Abstract

E-commerce competition has intensified in recent years, further raising the delivery speed and cost efficiency standards that companies must meet. The middle mile network that connects fulfillment centers to local distribution centers plays a decisive role in achieving these standards. In this paper, we study the Middle Mile Network Design Problem, which determines optimal network investments that balance the trade-off between fastest delivery speed and minimal operational costs. The problem requires computing truck schedules, shipment routes, and parcel flows through intermediate facilities subject to complex capacity constraints. Two key challenges make this problem computationally hard to solve for standard exact and heuristic approaches: (i) the use of complex black-box evaluations to predict operational outcomes, and (ii) problem instances involving over 200,000 commodities that must be solved within hours for operational planning. We propose a metaheuristic based on variable neighborhood search with specialized local search operators alongside lazy neighborhood evaluation that enable efficient exploration of the high-dimensional solution space. Our algorithm achieves up to 7.6% solution improvement over an incumbent heuristic while reducing runtime by up to 44%.

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Carlo S. Sartori, Jian Shen, Anastasia Kireeva, Mattia Neroni, and Philipp Loick. Large Scale Middle Mile Network Design Through Efficient Local Search. In 26th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2026). Open Access Series in Informatics (OASIcs), Volume 147, pp. 15:1-15:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{sartori_et_al:OASIcs.ATMOS.2026.15,
  author =	{Sartori, Carlo S. and Shen, Jian and Kireeva, Anastasia and Neroni, Mattia and Loick, Philipp},
  title =	{{Large Scale Middle Mile Network Design Through Efficient Local Search}},
  booktitle =	{26th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2026)},
  pages =	{15:1--15:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-453-6},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{147},
  editor =	{Cacchiani, Valentina and Funke, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2026.15},
  URN =		{urn:nbn:de:0030-drops-278110},
  doi =		{10.4230/OASIcs.ATMOS.2026.15},
  annote =	{Keywords: Network design, Middle mile logistics, Black-box evaluation, Local search, Variable Neighborhood Search}
}

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Large Scale Middle Mile Network Design Through Efficient Local Search

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