Talking Trucks: Decentralized Collaborative Multi-Agent Order Scheduling for Self-Organizing Logistics

Geert L.J. Pingen, Christian R. van Ommeren, Cornelis J. van Leeuwen, Ruben W. Fransen, Tijmen Elfrink, Yorick C. de Vries, Janarthanan Karunakaran, Emir Demirović, Neil Yorke-Smith

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Logistics planning is a complex optimization problem involving multiple decision makers. Automated scheduling systems offer support to human planners; however state-of-the-art approaches often employ a centralized control paradigm. While these approaches have shown great value, their application is hindered in dynamic settings with no central authority. Motivated by real-world scenarios, we present a decentralized approach to collaborative multi-agent scheduling by casting the problem as a Distributed Constraint Optimization Problem (DCOP). Our model-based heuristic approach uses message passing with a novel pruning technique to allow agents to cooperate on mutual agreement, leading to a near-optimal solution while offering low computational costs and flexibility in case of disruptions. Performance is evaluated in three real-world field trials with a logistics carrier and compared against a centralized model-free Deep Q-Network (DQN)-based Reinforcement Learning (RL) approach, a Mixed-Integer Linear Programming (MILP)-based solver, and both human and heuristic baselines. The results demonstrate that it is feasible to have virtual agents make autonomous decisions using our DCOP method, leading to an efficient distributed solution. To facilitate further research in Self-Organizing Logistics (SOL), we provide a novel real-life dataset.

Original languageEnglish
Title of host publicationProceedings of the 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022
EditorsAkshat Kumar, Sylvie Thiebaux, Pradeep Varakantham, William Yeoh
Place of PublicationPalo Alto
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Pages480-489
Number of pages10
ISBN (Print)978-1-57735-874-9
DOIs
Publication statusPublished - 2022
Event32nd International Conference on Automated Planning and Scheduling, ICAPS 2022 - Virtual, Online, Singapore
Duration: 13 Jun 202224 Jun 2022

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume32
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference32nd International Conference on Automated Planning and Scheduling, ICAPS 2022
Country/TerritorySingapore
CityVirtual, Online
Period13/06/2224/06/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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