An extended SECA-GDM method considering flexible linguistic scale optimization and its application in occupational health and safety risk assessment

Abstract

Experts have shifted from precise numerical representations to more complex linguistic representations in response to the growing complexity of occupational health and safety (OHS) risk assessment problems. However, there are more difficulties in accurately assessing risk when dealing with complex linguistic representations. Furthermore, in uncertain situations including complex linguistic representations, the multi-criteria decision-making (MCDM) approaches now in use for OHS risk assessment fail to synchronize the assessment of criteria and alternatives. To address these issues, this paper proposes a novel approach for OHS risk assessment that extends the idea of simultaneous evaluation of criteria and alternatives (SECA) to group decision-making (GDM) with complex linguistic representations. Firstly, flexible linguistic expressions (FLEs) are employed to represent experts’ complex linguistic risk assessments. Secondly, to accurately quantify the flexible linguistic assessment information, a numerical scale optimization model is constructed based on maximizing the closeness between individual and collective assessments, with the aim of obtaining the numerical scales of linguistic terms and flexible linguistic term sets. Then, an extended SECA-GDM method considering flexible linguistic scale optimization is proposed to simultaneously determine the risk criteria weights and priority order of occupational hazards. Finally, a case study is conducted to verify the effectiveness of the proposed method.

Keywords

• Occupational health and safety risk assessment
• Flexible linguistic expressions
• Numerical scale optimization
• Simultaneous evaluation of criteria and alternatives (SECA)
• Correlation measure