On the application of Valuation-Based Systems in the assessment of the probability bounds of Hazardous Material transportation accidents occurrence

Qiu, Siqi; Sacile, Roberto; Sallak, Mohamed; Schön, Walter

doi:10.1016/j.ssci.2014.08.006

Cited by 21 publications

(7 citation statements)

References 48 publications

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“…A multi-objective chance-constrained programming model was presented by considering uncertain conditions and a hybrid genetic algorithm was designed to effectively generate solutions as well. Based on the fundamental valuation theory and belief function theory, Qiu et al [24] evaluated the probability bounds of accidents occurrence. The valuation-based systems were applied to identify the factors, and the applicability and generality were demonstrated on a case study.…”

Section: Literature Reviewmentioning

confidence: 99%

Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm

Liu

2020

IET intell. transp. syst

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This paper takes the vehicles scheduling of hazardous materials as the research object. First, considered the four objectives of risk minimization, cost minimization, risk equilibrium value minimization, and duration minimization, the vehicles robust scheduling of hazardous materials in multiple distribution centers with risk balance is constructed. Then, uncertain models are transformed into peer-to-peer models through the idea of robust discrete optimization. By introducing the crossover and mutation operators of genetic algorithm into particle swarm algorithm, a hybrid particle swarm algorithm is constructed, and three-stage coding rules are adopted. Finally, case study is exemplified to prove the feasibility of the model and algorithm. The results show that the obtained scheduling scheme for the vehicles of hazardous materials minimizes the risk value and makes the risk distribution more balanced for the government regulatory department, and the vehicle can avoid certain road sections with relatively large risk values. For transportation enterprises, the vehicle scheduling scheme for transporting hazardous materials minimizes the cost and shortens the task duration at the same time. In the case of risk uncertainty, different robust control parameters are introduced to make the vehicles robust scheduling of hazardous materials have different degrees of stability.

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Section: Literature Reviewmentioning

confidence: 99%

Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm

Liu

2020

IET intell. transp. syst

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“…In the aspect of the analytical method of accident cause, Bu and other researchers have applied the fault tree analysis method to identify the risk sources (Bu et al, 2014);Bagheria has proposed the risk source identification model based on the consequences oftransportation accident (Bagheria et al, 2012);Zhanghas applied the method of analytic hierarchy process to establish the safety management evaluation model (Zhanget al,2009);Krejciassesses the risks through analyzing the load distribution of the risk levels (Krejci and Bambusek, 2012); Qiu has proposed the quantitative analysis method for transportation accidents of dangerous chemicals based on VBSS and the belief function theory (Qiu et al, 2015); Hu has analyzed the cause of transportation accidents of dangerous chemicals by means of the accident probability method (Hu and Cao 2015;Bonvicini and Spadoni, 2005).…”

Section: Literature Reviewmentioning

confidence: 99%

A Study on the Management Factors of Transportation Accidents of Dangerous Chemicals: from the Perspective of Bayesian Network

He¹

2016

Revista de la Facultad de Ingeniería

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Management directly impactsthe occurrence of the direct factors of the accidents.Unfulfilled management is the incentive of transportation accidents of dangerous chemicals. In order to investigate the influence path and the degree of the management factors in the accident cause system, with the help of the structural equation model, a hypothesis relationshipbetween the management factors and the influence of direct accident factors is constructed, analyzed and verified. Furthermore, via the Bayesian network model, the cause system is intuitively described, the posterior probability of each management factor under each state of the accidents is calculated, and suggestions are provided to reduce the accident rates and to strengthen the safety production management.

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“…Note that a bba m can equivalently be represented through a set of probability measures such that

P (m) = {P \in P_{normalΩ} | \forall A \subseteq Ω, P l (A) \geq P (A) \geq B e l (A)},

where P Ω is the set of all the probabilities that are compatible with the belief and plausibility functions. Thus, associated to each belief function, there is a closed convex set of probability measures of which a belief function is a lower bound.…”

Section: A Brief Introduction To Bugf Techniquementioning

confidence: 99%

Reliability analysis of multi‐state series systems with performance sharing mechanism under epistemic uncertainty

Qiu

Ming

2019

Quality & Reliability Eng

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For real engineering systems, it is sometimes difficult to obtain sufficient data to estimate the precise values of some parameters in reliability analysis. This kind of uncertainty is called epistemic uncertainty. Because of the epistemic uncertainty, traditional universal generating function (UGF) technique is not appropriate to analyze the reliability of systems with performance sharing mechanism under epistemic uncertainty. This paper proposes a belief UGF (BUGF)-based method to evaluate the reliability of multi-state series systems with performance sharing mechanism under epistemic uncertainty. The proposed BUGF-based reliability analysis method is validated by an illustrative example and compared with the interval UGF (IUGF)-based methods with interval arithmetic or affine arithmetic. The illustrative example shows that the proposed BUGF-based method is more efficient than the IUGF-based methods in the reliability analysis of multi-state systems (MSSs) with performance sharing mechanism under epistemic uncertainty.

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On the application of Valuation-Based Systems in the assessment of the probability bounds of Hazardous Material transportation accidents occurrence

Cited by 21 publications

References 48 publications

Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm

Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm

A Study on the Management Factors of Transportation Accidents of Dangerous Chemicals: from the Perspective of Bayesian Network

Reliability analysis of multi‐state series systems with performance sharing mechanism under epistemic uncertainty

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