Optimizing net-zero energy strategies in airports through a hybrid multi-method framework

Area of Science:

• Environmental Engineering
• Operations Research
• Sustainable Infrastructure

Background:

• Airports face increasing pressure to adopt sustainable practices and reduce carbon footprints.
• Evaluating energy retrofit strategies requires balancing environmental benefits with operational constraints and costs.
• Existing decision-making models may not adequately address the uncertainties inherent in complex infrastructure projects.

Purpose of the Study:

• To develop and validate a hybrid decision-making framework for prioritizing energy retrofit strategies in airport infrastructure.
• To integrate sustainability goals (energy savings, carbon reduction) with operational feasibility (cost, timeline, disruption).
• To provide actionable guidance for airport decision-makers investing in energy retrofits.

Main Methods:

• A hybrid framework combining Non-Dominated Sorting Genetic Algorithm II (NSGA-II), K-Means clustering, and Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP).
• Application to a mid-sized international airport scenario with defined budget, timeline, and disruption constraints.
• Evaluation of nine distinct retrofit strategies based on cost, energy savings, carbon reduction, implementation time, and operational disruption.

Main Results:

• Solution 9 emerged as the highest-priority strategy, offering 30% energy and carbon savings within the $1 million budget.
• Retrofit strategies were clustered into low-cost, balanced, and high-impact profiles based on performance and cost.
• Sensitivity analysis confirmed the robustness of the prioritization results under varying conditions.

Conclusions:

• The proposed hybrid framework effectively prioritizes energy retrofit strategies for airports, considering multiple conflicting objectives.
• The findings offer data-driven insights for strategic investment in sustainable airport operations, aligning with global climate goals.
• The framework supports progress towards net-zero operations by enabling informed decision-making for energy efficiency improvements.