Wind turbine airfoil design has historically targeted three objectives: high lift coefficient (<em>C<sub>L</sub></em>), high lift-to-drag ratio (<em>C<sub>L</sub>/C<sub>D</sub></em>), and insensitivity to leading-edge roughness (LER). The airfoils developed in the 1980s and 1990s for these objectives remain in widespread use today, yet the trade-offs among these competing goals have never been systematically mapped using modern global optimization methods. This paper develops a multi-objective evolutionary strategy (ES) to compute Pareto-optimal airfoil sets that reveal these trade-offs explicitly. The ES is initialized from a symmetric NACA airfoil rather than an existing wind turbine design, uses a Chebyshev-based CST parameterization, and is rigorously tuned via parameter studies. At the outer bounds of the Pareto front, the optimized airfoils improve upon the DU 93-210 reference by 87 % in <em>C<sub>L</sub></em>, 26 % in <em>C<sub>L</sub>/C<sub>D</sub></em>, and reduce ∆<em>C̄</em><sub><em>L</em>,LER</sub> to near zero. These gains are driven largely by increased camber; when a practical camber constraint of 5 % is applied, improvements of 33 % in <em>C<sub>L</sub></em> and 16 % in <em>C<sub>L</sub>/C<sub>D</sub></em> are still realized with near-complete LER insensitivity. A key finding is that, counter to conventional design wisdom, aft-loading correlates with reduced LER insensitivity for the optimized airfoils: roughness forces boundary-layer transition near the leading edge, producing a thicker turbulent boundary layer that separates earlier in the aft recovery region, negating the expected benefit of aft-loaded lift distributions. The framework, including the tuned ES and optimized airfoil database, is made available for public use.