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    Home»AI»A realistic instance generator for middle-mile logistics
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    A realistic instance generator for middle-mile logistics

    By RepublisherSeptember 18, 2026No Comments3 Mins Read
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    From Nature publication to catalyzing Computational Discovery
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    The logistics spectrum: First, last and middle mile

    The distinction between first-, middle- and last-mile logistics lies in the journey of an individual shipment. Throughout this journey, the primary operational goal is to efficiently use a fleet of vehicles to visit multiple locations. Consider the example of a manufacturer that sells goods on a typical online marketplace to reach individual consumers.

    In first- and last-mile logistics, a specific shipment remains in a single vehicle from its origin (the factory in the first mile, the distribution center in the last mile) to its destination (the distribution center in the first mile, the customer in the last mile). These VRPs involve optimizing a fleet of several vehicles over a limited time span, usually a single day. The optimization challenge is essentially one of assignment and sequencing: determining which vehicle handles which set of shipments, and in what order.

    In our example, the first mile corresponds to the collection of the items that have been sold by the manufacturer (e.g., pofferts) while the last mile covers the final delivery to the consumers (some of them being quite hungry!). In both cases, a single truck transports goods to or from the regional distribution center. However, if the manufacturer and the consumer are in different regions, middle-mile logistics bridge the gap between far-away distribution centers. For instance, goods from a manufacturer in Groningen (Netherlands) would first move to the regional distribution center in Utrecht, travel to another center in Paris (France) before being delivered to a consumer in Versailles.

    In contrast to the first and last mile, the middle mile functions as a relay race. A single shipment may be transported by several different vehicles across a continental network before reaching its final destination, maybe a week after departing. At intermediate distribution centers, the shipment may be unloaded, sorted by destination, and consolidated with other freight before being loaded onto the next vehicle. This creates a complex synchronization problem: the shipment must arrive at a distribution center within a specific time window to catch its scheduled outgoing truck. If it misses its scheduled connection, it will have to sit at the distribution center until the next cycle, leading to significant delays.

    In our example, once the manufacturer’s goods arrive in the Utrecht regional center, they are loaded onto the first truck for Antwerp (Belgium) to arrive the same day. Because the most immediate truck to Paris is full, and let’s say the customer opted for standard shipping, the goods take the second truck the following day from Antwerp to Paris. The parcel arrives in Paris on the night of the second day, where it enters the last-mile network for the final delivery to the customer the next day.



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