Scholarlink

<p>The increasing sophistication of cyberattacks necessitates adaptive and analytically robust mechanisms for cybersecurity strategy selection, a task that naturally constitutes a multi-criteria group decision-making (MCGDM) problem under uncertainty. To effectively capture the imprecision inherent in expert evaluations, this study employs the interval-valued (p,q)-rung orthopair fuzzy (IVpq-RF) framework, which provides greater representational flexibility than conventional interval-valued (q)-rung orthopair fuzzy sets. Within this setting, we construct generalized Dombi operational laws for IVpq-RF numbers and, on this basis, formulate novel aggregation operators, including the IVpq-RF generalized Dombi weighted average (IVpq-RFGDWA) and IVpq-RF generalized Dombi weighted geometric (IVpq-RFGDWG) operators, together with their ordered-weighted extensions. The theoretical properties and limiting cases of these operators are rigorously examined, enabling the development of a comprehensive MCGDM model for structured decision-making under uncertainty. A real-world case study on cybersecurity strategy evaluation demonstrates the practical utility of the proposed approach, while comparative and sensitivity analyses confirm its effectiveness, stability, and robustness in identifying optimal solutions within complex and uncertain environments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Analysis of generalized Dombi aggregation operators under interval-valued p,q-rung orthopair fuzzy sets with application to cybersecurity strategy selection

  • 期刊论文

  • 发表日期：

    2026年7月18日

查看全文
  • Jawad Ali

摘要

The increasing sophistication of cyberattacks necessitates adaptive and analytically robust mechanisms for cybersecurity strategy selection, a task that naturally constitutes a multi-criteria group decision-making (MCGDM) problem under uncertainty. To effectively capture the imprecision inherent in expert evaluations, this study employs the interval-valued (p,q)-rung orthopair fuzzy (IVpq-RF) framework, which provides greater representational flexibility than conventional interval-valued (q)-rung orthopair fuzzy sets. Within this setting, we construct generalized Dombi operational laws for IVpq-RF numbers and, on this basis, formulate novel aggregation operators, including the IVpq-RF generalized Dombi weighted average (IVpq-RFGDWA) and IVpq-RF generalized Dombi weighted geometric (IVpq-RFGDWG) operators, together with their ordered-weighted extensions. The theoretical properties and limiting cases of these operators are rigorously examined, enabling the development of a comprehensive MCGDM model for structured decision-making under uncertainty. A real-world case study on cybersecurity strategy evaluation demonstrates the practical utility of the proposed approach, while comparative and sensitivity analyses confirm its effectiveness, stability, and robustness in identifying optimal solutions within complex and uncertain environments.