This project will develop a package of planning products for radiation treatment that will introduce a measure of quality assurance now lacking, provide clinicians the opportunity to raise tumor dose, and expose the tradeoffs among the treatment constraints and objectives. The new approach based on mixed integer programming (MIP) will ensure that the dose distributions prepared for patients do not fail to meet the conditions specified because of inferior performance in a planning routine. The result will be a package for picking beams and beam angles, constructing intensity profiles, and evaluating the effect of uncertainties in treatment objectives or in target and organ positions. Constraints can include dose, dosevolume, and homogeneity limits, and restrictions on beam number. Phase I demonstrated the feasibility of using MIP to optimize tumor dose to within a known error of the best possible while enforcing prescribed constraints, and revealed the tradeoffs among the objective and constraints. Phase II aims to speed performance by customizing a proprietary solver to the developed algorithms and adding new formulations, to integrate the processes of intensity optimization and treatment delivery in order to limit the dose distortions users now face, and to engineer displays of the multidimensional tradeoffs present.