A Mobile Agent-Based Method for Logistics Coordination Management.

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Bibliographic Details
Title:	A Mobile Agent-Based Method for Logistics Coordination Management.
Authors:	Chen, Yong¹ 13507699675@163.com
Source:	International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 7, p168-182. 15p.
Subjects:	Logistics, Mobile agent systems, Scheduling, Drone aircraft, Decision making, Automated guided vehicle systems, Edge computing, Digital twin
Abstract:	To address the fundamental limitations of conventional logistics coordination systems--including delayed responses in dynamic environments, low collaboration efficiency, and rigid resource allocation--a cloud-edge-end collaborative mobile agent management framework for logistics scenarios was proposed by integrating recent advances in mobile agents, mobile edge computing, and digital twin technologies. This study introduced three major technical innovations. At the architectural level, a digital twin-driven, hierarchically decoupled open ecosystem was constructed, overcoming the constraints of traditional centralized control paradigms. At the mechanism level, a multimodal coordination mechanism was designed, achieving dynamic multi-issue task allocation, supporting context-aware adaptive decision-making, and enhancing the handling of complex problems. At the technical level, mobile edge computing-enabled task offloading strategies and lightweight real-time digital twin simulation were integrated to improve real-time responsiveness and reduce device energy consumption in mobile environments. To validate the effectiveness of the proposed framework, two representative experimental scenarios were constructed: a warehouse-distribution integrated automated guided vehicle coordination scenario and an urban last-mile hybrid delivery scenario involving unmanned aerial vehicles and automated guided vehicles. Comparative simulation experiments were conducted using an AnyLogic-ROS co-simulation platform. The results demonstrate that the proposed method significantly outperformed conventional centralized scheduling and standard multi-agent approaches in terms of end-to-end decision latency, task conflict resolution success rate, energy consumption, and adaptability to dynamic environments. These findings provide an innovative paradigm and robust technical support for the large-scale application of mobile agent technologies in logistics coordination management. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	To address the fundamental limitations of conventional logistics coordination systems--including delayed responses in dynamic environments, low collaboration efficiency, and rigid resource allocation--a cloud-edge-end collaborative mobile agent management framework for logistics scenarios was proposed by integrating recent advances in mobile agents, mobile edge computing, and digital twin technologies. This study introduced three major technical innovations. At the architectural level, a digital twin-driven, hierarchically decoupled open ecosystem was constructed, overcoming the constraints of traditional centralized control paradigms. At the mechanism level, a multimodal coordination mechanism was designed, achieving dynamic multi-issue task allocation, supporting context-aware adaptive decision-making, and enhancing the handling of complex problems. At the technical level, mobile edge computing-enabled task offloading strategies and lightweight real-time digital twin simulation were integrated to improve real-time responsiveness and reduce device energy consumption in mobile environments. To validate the effectiveness of the proposed framework, two representative experimental scenarios were constructed: a warehouse-distribution integrated automated guided vehicle coordination scenario and an urban last-mile hybrid delivery scenario involving unmanned aerial vehicles and automated guided vehicles. Comparative simulation experiments were conducted using an AnyLogic-ROS co-simulation platform. The results demonstrate that the proposed method significantly outperformed conventional centralized scheduling and standard multi-agent approaches in terms of end-to-end decision latency, task conflict resolution success rate, energy consumption, and adaptability to dynamic environments. These findings provide an innovative paradigm and robust technical support for the large-scale application of mobile agent technologies in logistics coordination management. [ABSTRACT FROM AUTHOR]
ISSN:	18657923
DOI:	10.3991/ijim.v20i07.61239