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

机译:用于海港码头在线集装箱堆放的多代理系统

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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,出现了与集装箱在码头中的存储有关的问题。这些问题在科学文献中被称为集装箱堆放问题(CSP),在于确定集装箱在码头的存储区域中的确切位置。已经进行了一些研究工作来开发用于管理容器存储操作的系统,这些系统被称为容器终端操作系统(CTOS)。不幸的是,现有系统受到与分布式控制,在线堆叠策略效率及其处理危险容器的能力有关的限制。在本文中,我们建议在不确定和受干扰的环境中,采用多主体方法对集装箱堆垛进行反应性和分散式控制。已经提出了信念-愿望-意向(BDI)模型来开发构成系统的不同代理。提出了一套用于干扰和被动决策管理的知识模型和学习机制,并将其集成到系统中。所建议的系统能够捕获,存储和重用知识,以便检测干扰(与资源分解相关的干扰),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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