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An Optimal Investment Scheduling Framework for Intelligent Transportation Systems Architecture

机译:智能交通系统体系结构的最优投资调度框架

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摘要

Transportation planning in general, and planning for intelligent transportation systems UTS in particular, are notable for multiple goals and for multiple constituencies. A review of the current literature offers several ITS investment evaluation methods that provide frameworks for the quantification of risks and benefits. Nevertheless,the traditional selection methods overemphasize quantitative and economic analysis and often neglect to consider qualitative and noneconomic data in the formal selection process. Furthermore, crisp data are fundamentally indispensable in tradinonal ITS investment selection methods. However, the data in real-world problems are often imprecise or ambiguous. In this article, we propose a novel fuzzy group multi-criteria framework for ITS investment evaluation and selection that aokes into consideration (1) the qualitative and quantitative criteria and their respective value judgments; (2) the verbal epres sions and linguistic variables for qualitative judgments which lead to ambiguity in the decision process; and (3) imprecise or vague judgments. First, we use fuzzy TOPSIS to calculate the fuzzy risk values with each ITS architecture subsystem. Next, we use fuzzy ROA to calculate the fuzzy real option values of the ITS subsystems. Last, we determine the optimal investment schedule for the ITS subsystems by considering the risk and option values as the coefficients of the objective [millions in a group multi-objective decision-making model.
机译:总体而言,交通规划尤其是针对智能交通系统UTS的规划对于多个目标和多个选区而言都是值得注意的。对现有文献的回顾提供了几种ITS投资评估方法,这些方法提供了量化风险和收益的框架。然而,传统的选择方法过分强调定量和经济分析,在形式选择过程中常常忽略了定性和非经济数据。此外,在传统的ITS投资选择方法中,基本数据是必不可少的。但是,实际问题中的数据通常不准确或模棱两可。在本文中,我们提出了一种用于ITS投资评估和选择的新型模糊群多标准框架,该框架引起了以下方面的考虑:(1)定性和定量标准及其各自的价值判断; (2)定性判断的语言表达和语言变量,导致决策过程中的歧义; (3)判断不准确或含糊不清。首先,我们使用模糊TOPSIS来计算每个ITS架构子系统的模糊风险值。接下来,我们使用模糊ROA来计算ITS子系统的模糊实物期权值。最后,我们通过将风险和期权价值视为一组多目标决策模型中目标的系数来确定ITS子系统的最佳投资计划。

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