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Multi-attribute decision-making approach for improvisational emergency supplier selection: Partial ordinal priority approach

Document Type

Research-Article

Author

Renlong Wang, Rui Shen, Shutian Cui, Xueyan Shao, Hong Chi, Mingang Gao

Journal Name

Expert Systems with Applications

Keywords

Adversarial hasse diagram, Improvisational emergency supplier selection, Multi-attribute decision-making, Partial ordinal priority approach, Partial-order relationship

Abstract

The unpredictable and complex nature of disasters underscores the need for a scientific and logical approach to improvisational emergency supplier selection (IESS), which is a typical multi-attribute decision-making problem. This study introduces Partial Ordinal Priority Approach (OPA-P) for IESS under information uncertainty and multi-stakeholder involvement. OPA-P contributes to a novel partial-order extension of Ordinal Priority Approach, emphasizing the necessity of Pareto-optimal analysis. It consists of two main steps: the first stage optimizes decision weights through a linear programming problem using easily accessible and stable ordinal preference information to simultaneously determine the weights of experts, attributes, and alternatives; the second stage generates the adversarial Hasse diagram for alternative comparison derived from the partial-order cumulative transformation set. This diagram streamlines the redundant dominance structure among alternatives and provides information on Pareto-optimal and suboptimal alternatives along with their clusters. The proposed approach is demonstrated through a case study on IESS for the Zhengzhou mega-rainstorm disaster with sensitivity and comparison analysis for model validation. Overall, the novelty of OPA-P lies in its ability to facilitate swift and stable decision-making while identifying potential Pareto-optimal solutions amidst high information uncertainty and multi-stakeholder involvement. © 2025 Elsevier Ltd

https://doi.org/10.1016/j.eswa.2025.128196

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