Original scientific paper

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.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

Abstract

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.

Keywords

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

Publication date:

25.7.2019.

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