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Optimization with fuzzy linear programming and fuzzy knowledge base

机译:模糊线性规划与模糊知识库的优化

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Due to the complexity of modern systems, a decision process is most often dependent at least in part on qualitative reasoning, especially in the case where human involvement is important. The paper proposes an optimization methodology-fuzzy linear programming coordinated with a fuzzy linguistic knowledge base-to handle quantitative and qualitative information simultaneously. In this approach, fuzzy linear programming is used to model quantitatively the basic resource constraints and objective functions, while a linguistic knowledge base is used to model imprecise human expertise. Freight train dispatching, in which a physical rail network is very complex and human expertise of a yardmaster plays an important role in decision making, illustrates the application.
机译:由于现代系统的复杂性,决策过程通常至少部分依赖于定性推理,尤其是在人类参与很重要的情况下。提出了一种优化方法-模糊线性规划与模糊语言知识库的协调配合-同时处理定量和定性信息。在这种方法中,模糊线性规划用于对基本资源约束和目标函数进行定量建模,而语言知识库用于对不精确的人类专业知识进行建模。货运列车调度说明了该应用,在该调度中,物理铁路网络非常复杂,而船长的人员专业知识在决策中起着重要作用。

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