<p>This research introduces a novel contribution to the Electric Vehicle Routing Problem (EVRP) field by addressing fuzzy demands, soft time windows, and recharging at demand points. The problem is formulated as a mixed-integer linear programming model that incorporates uncertainties in demand levels and allows flexibility in time windows with a penalty for its violation. LINGO software is utilized to solve the proposed model. To assess the effect of fuzzy demand, a parametric analysis is conducted by varying the fuzzy demand parameters using lexicographic fuzzy method implemented by LINGO. The model’s validity and effectiveness are verified using Solomon’s benchmark dataset, and further applied to a case study from the Egyptian local market. The solutions obtained are evaluated based on total costs incurred and total CO₂ emissions. By analyzing the resulting solutions, managerial implications are deduced, providing a framework for decision-makers in electric vehicle fleet management. Recommendations are made to decision makers on fuzzy demand modeling techniques, charging infrastructure, pricing and incentive strategies, and management systems. This study contributes to the advancement of EVRP research, offering practical solutions for real-world transportation planning and logistics management.</p>