Abstract: Online shopping optimization in the context of the present invention refers to making the optimal business decisions with regard to an online or electronic commerce purchase. One aspect of the present invention provides a method comprising extracting buyers' demand information from buyer-specified items or a previously-configured shopping cart and searching a product catalog that, when provided with the items specified or selected by the buyer, returns exact or equivalent items, such as replacement or substitute products. The method comprises formulating the online shopping decision-making problem into a mathematical programming model. The system systematically and quantitatively makes decisions for a buyer over various cataloged items in order to maximize or minimize an objective function subject to various constraints. Recommended optimized shopping carts are then presented to the buyer.

Abstract: Online shopping optimization in this context means, in general, making the optimal business decisions with regard to an online or electronic commerce purchase. The method begins with extracting buyer's demand information from buyer-specified items or a previously-configured shopping cart. It then includes a product catalog search that, when provided with the items specified or selected by the buyer, returns exact or equivalent (i.e., replacement or substitute) items. With the catalog search results, the online shopping optimization method formulates the online shopping decision-making problem into a mathematical programming model, particularly a mixed integer programming model. The method optimally decides, from the universe of vendors and items within the system: 1) from which of the various vendors to buy, 2) what identical, replacement, or substitute items to buy, 3) what package sizes of these items to buy, and 4) how many of each item to buy.