A robust risk analysis method for water resources allocation under uncertainty

Chen, C.; Huang, Guohe; Li, Y. P.; Zhou, Yang

doi:10.1007/s00477-012-0634-5

Cited by 30 publications

(17 citation statements)

References 35 publications

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“…Robustness refers to the ability of tolerating perturbations that might affect the system's functional body [29,30]. For EMS, it reflects the ability to provide medical rescue service when uncertainties occur.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

Zhang

Jia

Qin

2018

IJGI

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Abstract:It is important for station managers and emergency medical service (EMS) managers to understand the available ambulance stations for each metro station. EMS managers can make use of this information to reallocate EMS resources to improve the performance of EMS system. Station managers can pay attention to the safety management of metro stations with fewer medical rescue support. This paper aims to develop a selection diversity index to address two questions: "How many available ambulance stations are available or can serve the rescue of metro stations in emergency?" and "Which ambulance stations are most vulnerable?". To implement this measure in practice, definition of available ambulance stations for rescue of metro stations is described based on the response time threshold. The selection diversity is proposed to measure the preparability of medical rescue service for metro stations. To show proof of concept, a real-world case is presented to demonstrate the feasibility of the selection diversity index.

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Section: Literature Reviewmentioning

confidence: 99%

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

Zhang

Jia

Qin

2018

IJGI

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“…Over the past decades, a large number of inexact optimization methodologies have been proposed for tackling water resources management problems (Karamouz and Houck 1987;Reca et al 2001;Luo et al 2003;Huang and Chang 2003;Maqsood et al 2005;Xevi and Khan 2005;Ganji et al 2008;Li et al 2010;Fan et al 2012;He et al 2012;Shen et al 2012;Chen et al 2013;Tan et al 2013;Huang 2014, 2015). Among these approaches, two-stage stochastic programming (TSP) is an effective approach for addressing uncertainties expressed as random variables with known probability distributions.…”

Section: Introductionmentioning

confidence: 99%

A stochastic programming with imprecise probabilities model for planning water resources systems under multiple uncertainties

Wang

Huang

Wang

et al. 2015

Stoch Environ Res Risk Assess

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In this study, a stochastic programming with imprecise probabilities (SP-IP) model is proposed for planning water resources systems. The SP-IP model is capable of addressing multiple uncertainties in the forms of intervals with random boundaries and imprecise probability distributions. The stochastic optimization model can be transformed into a deterministic equivalence in a straightforward manner. A case study of regional water resources allocation is used to demonstrate the applicability of the proposed model. Results indicate that the total net benefits would be decreased with increased probabilities of occurrence, reflecting a potential trade-off between economic benefits and associated risks. The SP-IP model is also capable of providing a variety of decision alternatives under different scenarios of water policies, which is useful for water managers to formulate an appropriate water management policy in an uncertain environment.

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“…Mathematical analysis methods of risk assessment for the WRS are still developing rapidly, such as robust risk analysis method [79] , the chaotic method, genetic algorithm [80,81] , wavelet analysis, and the geographic information system.…”

Section: Mixed Methodsmentioning

confidence: 99%

Risk analysis methods of the water resources system under uncertainty

Gui¹,

Zhang²,

Li³

et al. 2015

Front. Agr. Sci. Eng.

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The main characteristic of the water resources system (WRS) is its great complexity and uncertainty, which makes it highly desirable to carry out a risk analysis of the WRS. The natural environmental, social economic conditions as well as limitations of human cognitive ability are possible sources of the uncertainties that need to be taken into account in the risk analysis process. In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS are discussed first, from both objective and subjective perspectives. Then the quantitative characterization methods of risk analysis are introduced, including three criteria (reliability, resiliency and vulnerability) and five basic optimization models (the expected risk value model, conditional value at risk model, chance-constrained risk model, minimizing probability of risk events model, and the multi-objective optimization model). Finally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized as random, fuzzy and mixed methods. A more comprehensive risk analysis methodology for the WRS is proposed based on the comparison of the advantages, disadvantages and applicable conditions of these three methods. This paper provides a decision support of risk analysis for researchers, policy makers and stakeholders of the WRS.

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A robust risk analysis method for water resources allocation under uncertainty

Cited by 30 publications

References 35 publications

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

A stochastic programming with imprecise probabilities model for planning water resources systems under multiple uncertainties

Risk analysis methods of the water resources system under uncertainty

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