Talking Trucks: Decentralized Collaborative Multi-Agent Order Scheduling for Self-Organizing Logistics
conference paper
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.
Topics
Autonomous agentsConstrained optimizationDecision makingHeuristic methodsInteger programmingMessage passingMulti agent systemsSchedulingSolsComplex optimization problemsConstraint optimization problemsDecentralisedDecision makersDistributed constraint optimizationsLogistics planningMulti agentOrder schedulingScheduling systemsSelf-organisingReinforcement learning
TNO Identifier
980750
ISSN
23340835
ISBN
9781577358749
Publisher
Association for the Advancement of Artificial Intelligence
Source title
Proceedings International Conference on Automated Planning and Scheduling, ICAPS, 32nd International Conference on Automated Planning and Scheduling, ICAPS 2022, 13 June 2022 through 24 June 2022
Pages
480-489
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