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Chinese Journal of Management Science ›› 2025, Vol. 33 ›› Issue (12): 121-133.doi: 10.16381/j.cnki.issn1003-207x.2023.1805

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Partial Ordinal Priority Approach Considering Pareto Optimal Identification for Multi-attribute Decision-making

Renlong Wang1, Rui Shen2, Hong Chi3,4, Xueyan Shao3, Mingang Gao3()   

  1. 1.School of Emergency Management Science and Engineering,University of Chinese Academy of Sciences,Beijing 100049,China
    2.School of Engineering Science,University of Chinese Academy of Sciences,Beijing 100049,China
    3.Institutes of Science and Development,Chinese Academy of Sciences,Beijing 100190,China
    4.School of Public Policy and Management,University of Chinese Academy of Sciences,Beijing 100049,China
  • Received:2023-10-31 Revised:2023-12-29 Online:2025-12-25 Published:2025-12-25
  • Contact: Mingang Gao E-mail:mggao@casisd.cn

Abstract:

The Partial Ordinal Priority Approach (OPA-P) for multi-attribute decision-making (MADM) is introduced in this study. This approach builds upon the Ordinal Priority Approach, with a linear optimization model for MADM weights based on partial order ranking. It utilizes a partial order accumulation transformation to create an adversarial Hasse diagram, portraying comparative advantages and disadvantages among alternatives. OPA-P concurrently derives weights for alternatives, criteria, and experts by incorporating expert preferences. By integrating the adversarial Hasse diagram, it identifies Pareto optimal alternatives and hierarchically classifies them, facilitating optimal selection. To assess the efficacy of the proposed approach, it focuses on evaluating spontaneous combustion hazards in Goaf areas, validating the approach by comparing it against relative research findings. In contrast to conventional MADM approaches, OPA-P leverages more stable and readily available partial order rankings as input data, making it better suited for contexts requiring precise decision-making data. Its outcomes exhibit heightened stability and adeptness in identifying potential Pareto solutions in MADM.

Key words: multi-attribute decision-making, partial ordinal priority approach (OPA-P), partial order relationship, adversarial Hasse diagram, Pareto optimal identification

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