A novel multi-objective optimization framework to allocate support funds for flash flood reduction based on multiple vulnerability assessment

Yang, Wei; Xu, Kui; Ma, Chao; Lian, Jijian; Jiang, Xuelian; Zhou, Ya-Dong; Bin, Lingling

doi:10.1016/j.jhydrol.2021.127144

Cited by 7 publications

(2 citation statements)

References 45 publications

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“…On this basis, we can establish a reasonable target model for the ISTP combined with the traffic environment of the studied area. (2) In recent years, many MOEAs have been tailored to solve the various optimization problems in real-world settings, e.g., network structure learning [24], reactive power dispatch [25], allocation support funds [26], relief distribution [27], and so forth. In addition, an AutoML approach using evolutionary algorithm has been proposed for EEG signal classification [28].…”

Section: Related Workmentioning

confidence: 99%

Multi-Objective Optimization Method for Signalized Intersections in Intelligent Traffic Network

Zhang

Fan

et al. 2023

Sensors

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Urban intersections are one of the most common sources of traffic congestion. Especially for multiple intersections, an appropriate control method should be able to regulate the traffic flow within the control area. The intersection signal-timing problem is crucial for ensuring efficient traffic operations, with the key issues being the determination of a traffic model and the design of an optimization algorithm. So, an optimization method for signalized intersections integrating a multi-objective model and an NSGAIII-DAE algorithm is established in this paper. Firstly, the multi-objective model is constructed including the usual signal control delay and traffic capacity indices. In addition, the conflict delay caused by right-turning vehicles crossing straight-going non-motor vehicles is considered and combined with the proposed algorithm, enabling the traffic model to better balance the traffic efficiency of intersections without adding infrastructure. Secondly, to address the challenges of diversity and convergence faced by the classic NSGA-III algorithm in solving traffic models with high-dimensional search spaces, a denoising autoencoder (DAE) is adopted to learn the compact representation of the original high-dimensional search space. Some genetic operations are performed in the compressed space and then mapped back to the original search space through the DAE. As a result, an appropriate balance between the local and global searching in an iteration can be achieved. To validate the proposed method, numerical experiments were conducted using actual traffic data from intersections in Jinzhou, China. The numerical results show that the signal control delay and conflict delay are significantly reduced compared with the existing algorithm, and the optimal reduction is 33.7% and 31.3%, respectively. The capacity value obtained by the proposed method in this paper is lower than that of the compared algorithm, but it is also 11.5% higher than that of the current scheme in this case. The comparisons and discussions demonstrate the effectiveness of the proposed method designed for improving the efficiency of signalized intersections.

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Section: Related Workmentioning

confidence: 99%

Multi-Objective Optimization Method for Signalized Intersections in Intelligent Traffic Network

Zhang

Fan

et al. 2023

Sensors

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“…Ecological vulnerability is a multidimensional and complex concept. Numerous assessment frameworks have been proposed to evaluate ecological vulnerability, including the Composite Index [24,25], the Pressure-Support-State-Response framework [26,27], the Driver-Pressure-State-Impact-Response framework [28,29], and the Exposure-Sensitivity-Adaptive Capacity framework [30][31][32]. Meanwhile, the EVA falls within the scope of the multiple-criteria decision analysis (MCDA) method.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-Based Ecological Vulnerability Assessment Driven by Human Impacts in China

2022

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Human activities have a significant impact on global ecosystems. Assessing and quantifying ecological vulnerability is a fundamental challenge in the study of the ecosystem’s capacity to respond to anthropogenic disturbances. However, little research has been conducted on EVA’s existing fuzzy uncertainties. In this paper, an ecological vulnerability assessment (EVA) framework that integrated the Exposure-Sensitivity-Adaptive Capacity (ESC) framework, fuzzy method, and multiple-criteria decision analysis (MCDA), and took into account human impacts, was developed to address the uncertainties in the assessment process. For the first time, we conducted a provincial-scale case study in China to illustrate our proposed methodology. Our findings imply that China’s ecological vulnerability is spatially heterogeneous due to regional differences in exposure, sensitivity, and adaptive capacity indices. The results of our ecological vulnerability assessment and cause analysis can provide guidance for further decision-making and facilitate the protection of ecological quality over the medium to long term. The developed EVA framework can also be duplicated at multiple spatial and temporal dimensions utilizing context-specific datasets to assist environmental managers in making informed decisions.

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The impact of tropical cyclones and water conservancy projects on island’s flash floods

Lian,

Li,

et al. 2024

Environ Sci Pollut Res

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A novel multi-objective optimization framework to allocate support funds for flash flood reduction based on multiple vulnerability assessment

Cited by 7 publications

References 45 publications

Multi-Objective Optimization Method for Signalized Intersections in Intelligent Traffic Network

Multi-Objective Optimization Method for Signalized Intersections in Intelligent Traffic Network

Fuzzy-Based Ecological Vulnerability Assessment Driven by Human Impacts in China

The impact of tropical cyclones and water conservancy projects on island’s flash floods

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