This paper is an exploration of numerical optimization as it applies to the consumer choice problem. Suggested algorithms are intended to compute solutions to the Marshallian problem, and some can extend to the dual given the suggested modifications. Each method seeks to either weaken the sufficient conditions for optimization, converge to a solution more efficiently, or describe additional properties of the decision space. The purpose of this paper is to explore constrained quasiconvex programming in a less complicated environment by design of Marshallian constraints.