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A multi agent system for the online container stacking in seaport terminals

机译:用于海港终端堆叠的在线集装箱的多代理系统

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With the continuous development of seaports, problems related to the storage of containers in terminals have emerged. Such problems, referred to in the scientific literature as Container Stacking Problems (CSP) consist in determining the exact location of containers in the storage area of a terminal. Several research works have been conducted to develop systems for the management of container storage operations, which are referred to as Container Terminal Operating Systems (CTOS). Unfortunately, existing systems suffer limitations related to distributed control, online stacking strategies efficiency and their ability to handle dangerous containers. In this paper, we suggest a multi-agent approach for the reactive and decentralized control of container stacking in an uncertain and disturbed environment. A Belief-Desire-Intention (BDI) model has been proposed for the development of the different agents constituting the system. A set of knowledge models and learning mechanisms for disturbance and reactive decision making management are suggested and integrated in the system. The suggested system is able to capture, store and reuse knowledge in order to detect disturbances (as those related to resources breakdown), select the most appropriate storage strategy and determine the most suitable container location. (C) 2019 Elsevier B.V. All rights reserved.
机译:随着海港的不断发展,出现了与终端终端集装箱储存有关的问题。在科学文献中称为容器堆叠问题(CSP)的这些问题包括在确定终端的存储区域中的容器的确切位置。已经进行了几项研究作品,以开发用于管理容器存储操作的系统,该系统被称为容器终端操作系统(CTO)。不幸的是,现有系统遭受与分布式控制相关的限制,在线堆叠策略效率及其处理危险集装箱的能力。在本文中,我们建议在不确定和受扰动的环境中对集装箱堆叠的反应和分散控制的多种代理方法。已经提出了一种信念 - 欲望 - 意图(BDI)模型是为了开发构成该系统的不同代理商。建议并在系统中建议并集成了一组知识模型和用于干扰和反应决策管理的学习机制。建议的系统能够捕获,存储和重复使用知识,以便检测干扰(如与资源崩溃相关的问题),选择最合适的存储策略并确定最合适的容器位置。 (c)2019 Elsevier B.v.保留所有权利。

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