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 language | English |
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Title of host publication | Proceedings of the 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022 |
Editors | Akshat Kumar, Sylvie Thiebaux, Pradeep Varakantham, William Yeoh |
Place of Publication | Palo Alto |
Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
Pages | 480-489 |
Number of pages | 10 |
ISBN (Print) | 978-1-57735-874-9 |
DOIs | |
Publication status | Published - 2022 |
Event | 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022 - Virtual, Online, Singapore Duration: 13 Jun 2022 → 24 Jun 2022 |
Publication series
Name | Proceedings International Conference on Automated Planning and Scheduling, ICAPS |
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Volume | 32 |
ISSN (Print) | 2334-0835 |
ISSN (Electronic) | 2334-0843 |
Conference
Conference | 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022 |
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Country/Territory | Singapore |
City | Virtual, Online |
Period | 13/06/22 → 24/06/22 |
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-careOtherwise 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.