Affiliations: [a] School of Civil Engineering, Southwest Jiaotong University, Chengdu, China
| [b] School of Civil Engineering, Chongqing University, China
| [c] School of Civil Engineering, Southwest Jiaotong University, Chengdu, China
| [d] Chengdu Liangzi Intelligent Technology Ltd, Chengdu, Sichuan, China
Correspondence:
[*]
Corresponding author. Tzu-Ping Lo, Chengdu Liangzi Intelligent Technology Ltd, No. 111, First Section, North of Second Ring Road, Chengdu, Sichuan, 610031, China. Cellphone: +86-18280009907; E-mail: [email protected].
Abstract: The construction industry has long been seen as a high-risk industry, and the risk evaluation method is the core of safety risk management. Complex construction environments can lead to risk evolution over time, leading to uncertainty in risk assessment. Therefore, it is necessary to establish a risk evaluation method for multi-period group decision, which can also deal with uncertain information reliably. This study defines the risk evaluation indicators for construction safety and adopts the cloud model to deal with the uncertain information of experts’ evaluations. A cloud-based aggregation algorithm is also employed for group decision. Then, a cloud-based Minkowski distance function is proposed to enhance the ability of TOPSIS to deal with the uncertain information. Finally, an optimization algorithm is used to calculate the multi-period comprehensive evaluation value to define the risk priority. A real case is used for demonstration and the results show that the proposed method can effectively deal with the risk evaluation problem of multi-project, multi-period and group decision with uncertain information.
Keywords: Construction safety risk, cloud model, TOPSIS, uncertain
information
