@misc{Fernández-Fernández_Yasmany_Bridging,
 author={Fernández-Fernández, Yasmany and Allende Alonso, Sira M. and Miranda Pérez, Ridelio and Bouza Allende, Gemayqzel},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={Hurricane evacuation planning under uncertainty requires integrating decisions across multiple spatial and temporal scales, yet the literature addresses demand stochasticity, temporal robustness, and computational tractability largely in isolation.},
 abstract={This paper develops a unified optimization framework organized around six progressive layers: meteorological scenario generation, deterministic and stochastic network flow planning, vehicle scheduling with origin-based decomposition, classical robust temporal protection, neutrosophic adaptive robust optimization with scenario-anchored uncertainty sets, and computational complexity characterization.},
 abstract={An integrated critical review of 337 Scopus-indexed publications (2022-2026) identifies persistent methodological gaps that motivate each architectural layer. The framework couples two-stage stochastic programming with budget-constrained robust optimization, affine decision rules, and neutrosophic indeterminacy calibration within a single operational pipeline.},
 abstract={Validation on a georeferenced Caribbean network demonstrates a 94% reduction in binary variables through origin-based decomposition and end-to-end execution in under four minutes, with a sensitivity analysis showing that neutrosophic budget calibration reduces the price of robustness from 24.8% to 2.8%.},
 title={Bridging stochastic, robust, and neutrosophic paradigms for hurricane evacuation under compound uncertainty: A six-layer methodological synthesis},
 type={artykuł},
 keywords={hurricane evacuation, robust optimization, stochastic programming, neutrosophic uncertainty sets, hierarchical decomposition},
}