Importance

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Abstract

A computer-implemented method involves modeling of product decisions in a retail store. The product decision variables are profit, assortment, placement, promotion, and inventory. Various rules and constraints such as facing elasticity, shelf replenishment costs, shelf space, carrying costs, facing capacity, slotting fees, and cannibalization are defined for multiple product decision variables. An objective function utilizes the rules and constraints for the multiple product decision variables. Other product parameters are organized into a hierarchal structure. A function is defined for each product parameter and a control variable is selected to control each product parameter function. The hierarchical structure can use brand hierarchy, enterprise hierarchy, or customer buying decisions. The objective function simultaneously models each of the multiple product decision variables by iteratively resolving the objective function into values which optimize sales, revenue, and profit for the retail store. The model is output in graphic format.

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First Claim