Designing strategic scenarios is crucial for ensuring organizational resilience and competitiveness in today's volatile business environments. Scenario design has matured as a cognitive tool for exploring and preparing for plausible futures. Recent studies emphasize organizational and procedural aspects, such as leadership's role and the importance of stakeholder engagement in creating meaningful scenarios. This study introduces a novel approach by developing a Hybrid Fuzzy Model that intelligently integrates advanced Artificial Intelligence (AI) algorithms with foresight methodologies and expert knowledge. The model is built upon a robust quantitative-qualitative framework, employing techniques such as fuzzy logic, the Adaptive Neuro-Fuzzy Inference System (ANFIS), the Delphi method, and multi-objective Pareto optimization. A critical review of the literature from 2019–2024 identified significant gaps in existing approaches, which this model is designed to address. For operational validation, the model was implemented using simulated real-world data from Iran's strategic zinc industry. Comprehensive quantitative and qualitative validation results—including model performance metrics (R^2 = 0.968), Delphi convergence charts, optimized membership functions, and the Pareto front of optimal scenarios—confirm the model's high accuracy and remarkable effectiveness in managing complex uncertainties and generating robust strategic scenarios. This research provides managers and policymakers with an advanced analytical tool to make more informed, flexible, and robust strategic decisions amidst future complexities, thereby ensuring organizational agility.

نویسندگان

کلمات کلیدی:

Software Testing, Test Case Prioritization, Machine Learning Techniques, Unit Test Optimization, Metaheuristic Methods

چکیده

Designing strategic scenarios is crucial for ensuring organizational resilience and competitiveness in today's volatile business environments. Scenario design has matured as a cognitive tool for exploring and preparing for plausible futures. Recent studies emphasize organizational and procedural aspects, such as leadership's role and the importance of stakeholder engagement in creating meaningful scenarios. This study introduces a novel approach by developing a Hybrid Fuzzy Model that intelligently integrates advanced Artificial Intelligence (AI) algorithms with foresight methodologies and expert knowledge. The model is built upon a robust quantitative-qualitative framework, employing techniques such as fuzzy logic, the Adaptive Neuro-Fuzzy Inference System (ANFIS), the Delphi method, and multi-objective Pareto optimization. A critical review of the literature from 2019–2024 identified significant gaps in existing approaches, which this model is designed to address. For operational validation, the model was implemented using simulated real-world data from Iran's strategic zinc industry. Comprehensive quantitative and qualitative validation results—including model performance metrics (R^2 = 0.968), Delphi convergence charts, optimized membership functions, and the Pareto front of optimal scenarios—confirm the model's high accuracy and remarkable effectiveness in managing complex uncertainties and generating robust strategic scenarios. This research provides managers and policymakers with an advanced analytical tool to make more informed, flexible, and robust strategic decisions amidst future complexities, thereby ensuring organizational agility.

مراجع

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Naji، E.، Najafi، A.، و Ehtesham Rasi، R. (2026). Designing strategic scenarios is crucial for ensuring organizational resilience and competitiveness in today’s volatile business environments. Scenario design has matured as a cognitive tool for exploring and preparing for plausible futures. Recent studies emphasize organizational and procedural aspects، such as leadership’s role and the importance of stakeholder engagement in creating meaningful scenarios. This study introduces a novel approach by developing a Hybrid Fuzzy Model that intelligently integrates advanced Artificial Intelligence (AI) algorithms with foresight methodologies and expert knowledge. The model is built upon a robust quantitative-qualitative framework، employing techniques such as fuzzy logic، the Adaptive Neuro-Fuzzy Inference System (ANFIS)، the Delphi method، and multi-objective Pareto optimization. A critical review of the literature from 2019–2024 identified significant gaps in existing approaches، which this model is designed to address. For operational validation، the model was implemented using simulated real-world data from Iran’s strategic zinc industry. Comprehensive quantitative and qualitative validation results—including model performance metrics (R^2 = 0.968)، Delphi convergence charts، optimized membership functions، and the Pareto front of optimal scenarios—confirm the model’s high accuracy and remarkable effectiveness in managing complex uncertainties and generating robust strategic scenarios. This research provides managers and policymakers with an advanced analytical tool to make more informed، flexible، and robust strategic decisions amidst future complexities، thereby ensuring organizational agility. علم تصمیم گیری و سیستم های هوشمند، 3(1)، 1-10. https://www.dsisj.com/index.php/dsisj/article/view/57

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