Abstract: The embodiments described herein can provide systems and methods for optimizing prizes. Specifically, these systems and methods utilize competitive history data to provide improved pricing recommendations for sellers. This competitive history data can include a time series of one or more competitor's prices for a set of products. The systems and methods described herein can use this competitor price data with a corresponding time series of seller's data on their product prices and resulting demand to provide improved pricing recommendations to the seller. This use of competitive history data to provide improved pricing recommendations to sellers introduces significant complexity to the optimization of prices. Specifically, this use of competitive history data introduces significant non-convexity to the determination of pricing recommendations.

Abstract: The embodiments described herein can provide systems and methods utilize competitive history data to provide improved pricing recommendations for sellers. This competitive history data can include a time series of one or more competitor's prices for a set of products. This use of competitive history data to provide improved pricing recommendations to sellers introduces significant non-convexity to the determination of pricing recommendations. Accordingly, the systems and methods described herein employ a variety of technical approaches to generating the price recommendations in light of this introduced complexity. Additionally, the systems and methods employ various techniques to providing these price recommendations even when competitive history data is limited. Specifically, by using the limited to competitive history data to generate constraints, where the constraints can then be used for additional price optimizations where competitive history data is unavailable.

Abstract: Methods and systems for calculating parameters for a transaction that includes item purchase, item storage, and item sale, by receiving input parameters related to the transaction and executing a software module that is responsive to at least some of the input parameters to concurrently calculate optimized or maximized output transaction parameters comprising purchase cost of items, selling price of items, and item inventory forecasts, while meeting tradeoffs between or among, and meeting constraints relating to, the output parameters.