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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Talking Trucks

Authors: Pingen, Geert; Van Ommeren, Christian; Van Leeuwen, Coen; Fransen, Ruben; Elfrink, Tijmen; De Vries, Yorick; Janarthanan Karunakaran; +2 Authors
Abstract

Talking Trucks dataset (v2021.12) This dataset is used for research into Self-organizing logistics and published as part of the paper "Talking Trucks: Decentralized Collaborative Multi-Agent Order Scheduling for Self-Organizing Logistics". It is managed by the TNO Sustainable Transport and Logistics department. Please contact Christian van Ommeren (christian.vanommeren@tno.nl) and Ruben Fransen (ruben.fransen@tno.nl) for details. The dataset contains 4 types of objects (files): agents, orders, route stops, and locations; and currently holds data for three experiments, represented by a UUIDv4 identifier. Agents Represents an agent that is able to transport load and is to be assigned to specific orders. This file contains the agent's unique UUIDv4 identifier; agent type; Euronorm emission norm; agent cost for driving a km in EUR; agent cost per hour in EUR; working hours start and end times; and agent starting coordinates. Orders Represents the unit that should be transported by the agents. This file contains the order's unique UUIDv4 identifier; container type; TEU; trade type (import/export); and weight. Route stops Represents the stop which is associated with an order. Stops are tied to a real-world location. This file contains the route stop's unique UUIDv4 identifier; stop index; location UUIDv4 identifier; type (origin/destination); order UUIDv4 identifier; and time window times. Locations Represents a real-world location at which logistics operations take place (for a specific duration). This file contains the location's unique UUIDv4 identifier; country designator; coordinates; Euronorm emission norm; stop duration; and service type (decoupling, live handling, craning, ...). License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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Keywords

Self-organizing Logistics, Container scheduling, Collaborative Decision-making, Multi-agent systems, Decentralized Decision-making, DCOP, Logistics, Distributed Constraint Optimization, Reinforcement Learning, Digital Twins, Order scheduling

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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