Analyzing Dynamics of a Supply Chain Using Logic-Based Genetic Programming
Analyzing Dynamics of a Supply Chain Using Logic-Based Genetic Programming
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DOI：
10.1007/978-3-540-30132-5_66
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发表时间：
2004-09
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影响因子：
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通讯作者：
Ken Taniguchi;T. Terano
中科院分区：
文献类型：
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作者：
Ken Taniguchi;T. Terano
本文提出了基于代理制定的供应链管理（SCM）系统的制造企业。我们将每个公司建模为智能代理，通过分布式人工智能中的黑板架构相互通信。为了克服传统供应链管理系统的问题，我们采用了信息熵的概念，它代表了每个公司的采购，销售和库存活动的复杂性。基于这一思想，我们实现了一个基于代理的模拟器，学习“好”的决策viagenetic编程在逻辑编程环境。通过大量的实验，我们的模拟器对动态环境的变化表现出良好的性能。
This paper proposes agent-based formulation of a Supply Chain Management (SCM) system for manufacturing firms. We model each firm as an intelligent agent, which communicates each other through the black-board architecture in distributed artificial intelligence. To overcome the issues of conventional SCM systems, we employ the concept of information entropy, which represents the complexity of the purchase, sales, and inventory activities of each firm. Based on the idea, we implement an agent-based simulator to learn ‘good’ decisions viagenetic programming in a logic programming environment. From intensive experiments, our simulator have shown good performance against the dynamic environmental changes.