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This research presents a sophisticated method for optimizing Unmanned Aerial Vehicle (UAV) landing zone selection and payload delivery in flood disaster responses. We propose the Spherical Fuzzy-Measurement of Alternatives and Ranking according to the COmpromise Solution (SF-MARCOS) technique for addressing the decision-making uncertainties. Criteria, including safety, visibility, communication range, emergency landing options, surface and terrain conditions, wind factors, altitude, and proximity to the disaster, undergo linguistic assessments with decision-makers. The method, tailored for multiple decision-makers, carefully balances ideal and anti-ideal trade-offs using the Spherical Weighted Arithmetic Mean (SWAM) operator. Resulting in a comprehensive ranking of landing zones and payload delivery strategies, this study underscores stakeholder perspectives’ significance and criteria importance. Sensitivity analyses ensure adaptability to diverse disaster scenarios, enhancing reliability. This research contributes significantly to disaster management, logistics efficiency, and data-driven decision-making.

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A Spherical Fuzzy-MARCOS-Based Decision-Making Model for Optimizing UAV Landing Zone Selection and Payload Delivery

  • 章节

  • 发表日期：

    2026年

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  • Saptadeep Biswas,
  • Rajdip Mahajan,
  • Abhijit Baidya,
  • Uttam Kumar Bera

摘要

This research presents a sophisticated method for optimizing Unmanned Aerial Vehicle (UAV) landing zone selection and payload delivery in flood disaster responses. We propose the Spherical Fuzzy-Measurement of Alternatives and Ranking according to the COmpromise Solution (SF-MARCOS) technique for addressing the decision-making uncertainties. Criteria, including safety, visibility, communication range, emergency landing options, surface and terrain conditions, wind factors, altitude, and proximity to the disaster, undergo linguistic assessments with decision-makers. The method, tailored for multiple decision-makers, carefully balances ideal and anti-ideal trade-offs using the Spherical Weighted Arithmetic Mean (SWAM) operator. Resulting in a comprehensive ranking of landing zones and payload delivery strategies, this study underscores stakeholder perspectives’ significance and criteria importance. Sensitivity analyses ensure adaptability to diverse disaster scenarios, enhancing reliability. This research contributes significantly to disaster management, logistics efficiency, and data-driven decision-making.