A Fuzzy Multi Objective Optimization Model For A Sustainable And Competitive Uav Delivery Network Under Uncertainty

This paper presents a fuzzy multi-objective optimization model for the Green Location-Routing Problem (GLRP) in competitive UAV delivery networks. The model simultaneously optimizes total cost, carbon emissions, and service time while determining facility locations and UAV routes under realistic constraints: capacity, energy, and no-fly zones. To address inherent uncertainties in customer demand and travel times, we develop a fuzzy logic framework that generates robust Pareto-optimal solutions for different confidence levels (α). The resulting fuzzy model is solved using three meta-heuristic algorithms: NSGA-II, MOACO, and MOSA. Numerical results demonstrate that the proposed fuzzy approach yields a more practical and cost-effective design compared to deterministic models, effectively balancing economic and environmental objectives under uncertainty. This study offers logistics managers a robust decision-support tool for sustainable UAV network deployment.