A data-based approach for solving the Rank Pricing Problem.

Abstract

The Rank Pricing Problem is a challenging mixed-integer optimization problem. It aims to determine the optimal pricing strategies of a set of products ranked by customer preferences. Given its NP-hard nature, existing literature offers various exact methodologies. However, these approaches can be intricate to formulate and computationally intensive. In contrast, in this talk, we propose a novel data-based methodology that is simple but effective. Even though our heuristic proposal cannot guarantee to obtain the optimal solution, the numerical results in different instances show its capacity to deliver high-quality results, providing a pragmatic alternative within a short computational timeframe.