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The human-machine interface’s quality is a critical determinant influencing system usability and user experience. This study proposes an integrated evaluation model combining the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which aims to overcome the limitations of intense subjectivity and multidimensional criteria in conventional evaluation methods. Initially, an evaluation index system was established using AHP, and the criteria weights were calculated. Subsequently, the TOPSIS method was applied to calculate the relative closeness between each solution and the ideal solution, enabling quantitative ranking of the interface. The effectiveness and practicability of the model are verified through the application of actual cases. The research results show that the AHP-TOPSIS integrated evaluation model provides quantifiable decision-making support for interface design, assisting designers in optimizing interface solutions.

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A Human-Machine Interface Evaluation Method Integrating AHP and TOPSIS

  • 会议论文

  • 发表日期：

    2026年

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  • Jianke Hong,
  • Qiyun Fang,
  • Lian Liu,
  • Gezhi Yan

摘要

The human-machine interface’s quality is a critical determinant influencing system usability and user experience. This study proposes an integrated evaluation model combining the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which aims to overcome the limitations of intense subjectivity and multidimensional criteria in conventional evaluation methods. Initially, an evaluation index system was established using AHP, and the criteria weights were calculated. Subsequently, the TOPSIS method was applied to calculate the relative closeness between each solution and the ideal solution, enabling quantitative ranking of the interface. The effectiveness and practicability of the model are verified through the application of actual cases. The research results show that the AHP-TOPSIS integrated evaluation model provides quantifiable decision-making support for interface design, assisting designers in optimizing interface solutions.