SmartCart: A consolidated shopping cart for pareto-optimal sourcing and fair discount distribution

This paper explores two interrelated questions: First, when buyers form a coalition to obtain volume discounts on the purchase of multiple items from multiple sellers, how many of each item should be purchased from each seller to maximize the overall discount? Secondly, when this discount is obtained successfully, how should it be allocated to the buyers who pooled their resources to make one successful group purchase? An auction is the context under which these questions are tested, using a scenario in which multiple buyers form a coalition to consolidate their individual shopping carts into one aggregated shopping cart. A relational database is used to simulate an interactive auction and tracks buyers, sellers, items, prices before discount, prices after discount, purchase decisions, and other key data. When a critical mass of items to be ordered is reached, the shopping carts are locked and the coalition´s overall demand for each item is copied to an aggregated shopping cart. To clear the auction, a decision guidance query language (DGQL) is executed to determine, using a MILP optimization, the quantity of each item to be ordered from each supplier to maximize discounts. A formula that allocates discounts to members of the buying coalition is then proposed. DGQL provides a great degree of flexibility and extensibility in the specification of constraints using a high-level language that can be embedded directly in SQL. This analysis provides a foundation from which a working tool could be built to allow buyers to form ad hoc purchasing coalitions to achieve discounts that otherwise would be unavailable to the individual buyers acting in isolation.