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基于模糊层次分析法和动态狄克斯特拉模拟的可持续交通系统自适应决策支持模型。

Adaptive decision support model for sustainable transport system using fuzzy AHP and dynamical Dijkstra simulations.

机构信息

School of Cyber Science and Engineering, Sichuan University, Chengdu 610065, China.

School of Computer Science, University of Birmingham, Birmingham 35201, UK.

出版信息

Math Biosci Eng. 2022 Jul 11;19(10):9895-9914. doi: 10.3934/mbe.2022461.

DOI:10.3934/mbe.2022461
PMID:36031974
Abstract

Concerning decisions for modern public transportation project, the lack of consensus between stakeholders and foreseeability of future transportation requirements might cause poor sustainability of the project. Unfortunately, many decision models give decision opinions without the test of the sustainability. Therefore, a dynamical Dijkstra simulation model is proposed to simulate the real traffic flows. In the model, the cost of the road connections is dynamically updated according to the change of the passenger flows. Then a combined decision support model using fuzzy AHP and dynamical Dijkstra simulation tests is designed. The combined model is capable of analyzing and creating consensus among different stakeholder participants in a transport development problem. The application of FAHP and dynamical Dijkstra ensures that the consensus creation is not only based on the FAHP decision making process but also on the response of the simulated execution of the decisions by dynamical Dijkstra. Thus, the decision makers by FAHP can firstly make their initial preferences in transportation planning, given the pairwise comparison matrices and generate the related weight for the traffic control parameters. And the dynamical Dijkstra simulations test the plan's setting and gives a response to iteratively adjust the FAHP matrices and parameters. The combined model is tested in different scenarios. And the results show that by the application of the proposed model, decision-makers can be more aware of the conflicts of interests among the involved groups, and they can pay more attention to possible violations causing by the change of traffic environment, including the citizen numbers, the construction cost, the roll cost, and etc., to get a more sustainable plan.

摘要

关于现代公共交通项目的决策,利益相关者之间缺乏共识和对未来交通需求的可预测性可能导致项目的可持续性较差。不幸的是,许多决策模型在没有可持续性测试的情况下给出决策意见。因此,提出了一种动态的迪杰斯特拉模拟模型来模拟真实的交通流量。在该模型中,根据客流量的变化,动态更新道路连接的成本。然后,设计了一个使用模糊层次分析法和动态迪杰斯特拉模拟测试的组合决策支持模型。该组合模型能够分析和创建不同利益相关者参与者在交通发展问题中的共识。使用 FAHP 和动态迪杰斯特拉确保共识的创建不仅基于 FAHP 决策过程,还基于动态迪杰斯特拉对决策模拟执行的响应。因此,FAHP 的决策者可以首先在交通规划中根据成对比较矩阵做出他们的初始偏好,并为交通控制参数生成相关权重。而动态的迪杰斯特拉模拟测试计划的设置并给出响应以迭代调整 FAHP 矩阵和参数。该组合模型在不同场景下进行了测试。结果表明,通过应用所提出的模型,决策者可以更清楚地了解所涉及群体之间的利益冲突,并且可以更加关注可能因交通环境变化而导致的违规行为,包括公民数量、建设成本、滚动成本等,以制定更可持续的计划。

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