Strategic retrofit decision modeling for net-zero airport energy systems: Hybrid optimization and policy simulation at Istanbul airport
Energy Strategy Reviews, cilt.65, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 65
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.esr.2026.102186
- Dergi Adı: Energy Strategy Reviews
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Anahtar Kelimeler: Airport energy retrofit, Entropy-pythagorean fuzzy AHP (entropy-PFAHP), Hybrid weighting, Istanbul airport, K-means clustering, NSGA-II, Policy scenario simulation, Sensitivity analysis (tornado & Monte Carlo)
- Kocaeli Üniversitesi Adresli: Evet
Özet
This study develops an integrated hybrid decision-support framework for strategic energy retrofit planning in large-scale airport infrastructure under uncertainty, using Istanbul Airport as a real-world case. The method integrates stochastic multi-objective optimization using NSGA-II, applies K-Means clustering with hierarchical validation to profile Pareto-optimal retrofit portfolios, and employs hybrid Entropy–Pythagorean Fuzzy AHP (Entropy-PFAHP) to combine expert judgment with objective, data-driven dispersion in criteria weights. Portfolios are evaluated using investment cost, energy savings, carbon reduction, operational disruption, and implementation time, and uncertainty is tested through scenario-based simulations and robustness analysis. The results identify three strategy typologies with clear performance–cost trade-offs: cost-efficient portfolios deliver ∼20% energy savings and ∼15% carbon reduction with an investment of ∼USD 870,000; balanced portfolios deliver 22.5–25% energy savings and 18–22% carbon reduction with investments of USD 887,500–925,000; and high-impact portfolios achieve up to ∼30% energy savings and ∼30% carbon reduction with investments of USD 943,750–1,000,000. Under Monte Carlo uncertainty, the high-impact cluster remains dominant in 89.4% of simulation runs, indicating strong robustness of decarbonization-focused portfolios under plausible parameter variability. This study's novelty is the delivery of a single, end-to-end, policy-responsive workflow that (i) generates retrofit portfolios via stochastic Pareto optimization (NSGA-II), (ii) converts complex Pareto sets into decision-ready strategy typologies via validated clustering, and (iii) produces uncertainty-tested prioritization by integrating objective entropy weights with expert-based fuzzy weighting (Entropy-PFAHP) within one coherent framework for airport retrofit decision-making.