In artillery fires, the use of multiple aimpoints can spread damage over a large area when a unitary target location is inaccurate or when a collection of enemy targets span an area. Little research exists for computing an optimized pattern of aimpoints to maximize lethality. Current methods includes only basic geometric shapes and software solutions that are often hard-coded and scaled for these simple target areas. Since processing is not a major issue in modern computing, dynamic solutions are obtainable for irregular geometries and clustering of enemy detections. This research is a mathematical optimization solution that demonstrates how to tailor aimpoint configurations to complex area targets. Several factors are weighed when generating these aimpoint configurations including the target-weight density function, weapon accuracy, type of damage, and radius of effects. The goal of this research is to reach greater effectiveness against complex area targets with fewer rounds—saving the military the extensive logistic transportation requirements and ammunition costs.