1. A method comprising: at least one computer processor formulating a linear optimization problem with a plurality of variables and that takes into account at least: a plurality of customer constraints stored in computer storage and comprising at least one of an eligibility condition constraint, a peer group logic constraint, and a maximum number of offers constraint; and a plurality of economic, business, or consumer constraints stored in computer storage, wherein each constraint is reflective of an economic goal of a business to consumer decisioning strategy; the computer processor reducing the linear optimization problem to a non-linear problem with a feasible number of dimensions, wherein the non-linear problem is mathematically equivalent to the linear optimization problem; and the computer processor selecting a business to consumer decisioning strategy with desired expected utility and that satisfies the constraints at least in part by iteratively solving the non-linear problem on a sample of customers within a pre-defined tolerance, wherein the selected consumer decisioning strategy identifies specific customers that are to receive specific decision options, and wherein the non-linear problem takes into account at least: a plurality of behavioral probabilities that each represent a probability that a specific customer will respond to a specific decision option; and a plurality of profitabilities that each represent a profitability resulting from a specific customer responding to the specific decision option.