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https://doi.org/10.17559/TV-20190703194602

Optimal Routing for Safe Construction and Demolition Waste Transportation: A CVaR Criterion and Big Data Analytics Approach

Ying Qiu orcid id orcid.org/0000-0002-4716-4454 ; Beijing Institute of Petrochemical Technology, School of Economics and Management, No.19 Qingyuan North Road, Daxing District, 102617, Beijing, China
Xinna Zhao ; Beijing Institute of Petrochemical Technology, School of Economics and Management, No.19 Qingyuan North Road, Daxing District, 102617, Beijing, China
Xiaohong Zhang ; Beijing Institute of Petrochemical Technology, School of Economics and Management, No.19 Qingyuan North Road, Daxing District, 102617, Beijing, China


Puni tekst: engleski pdf 1.483 Kb

str. 1128-1135

preuzimanja: 610

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Sažetak

Rapid urbanisation worldwide, especially in developing countries and areas, has led to the generation of large amounts of construction and demolition waste (C&DW). The resultant transportation demands pose severe threats to safe transportation and secure city operation. By considering the low-probability–high-consequence nature of C&DW traffic accidents and the effectiveness of route optimisation in transportation risk control, a risk-averse project was implemented. Furthermore, an optimal routing model based on the conditional value at risk (CVaR) criterion is proposed. The model considered various risk-averse attitudes of decision-makers. For practicality and for strongly supporting policy-making, big data technology, including the construction of multistructure databases and in-depth analysis, was applied to achieve the proposed CVaR routing model. Therefore, the present study extended the CVaR method to optimal routing design in the field of safe urban C&DW transportation and integrated the optimal model with big data technology.

Ključne riječi

big data technology; conditional value at risk (CVaR); construction and demolition waste (C&DW); risk-averse attitude; routing

Hrčak ID:

223315

URI

https://hrcak.srce.hr/223315

Datum izdavanja:

25.7.2019.

Posjeta: 1.358 *