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1934. A data-based approach for solving the Rank Pricing Problem
Invited abstract in session WD-27: Machine Learning for and with Mathematical Optimization, stream Mathematical Optimization for XAI.
Wednesday, 14:30-16:00Room: 047 (building: 208)
Authors (first author is the speaker)
| 1. | M. Asuncion Jimenez-Cordero
|
| Statistics and Operations Research, University of Malaga | |
| 2. | Salvador Pineda Morente
|
| Electrical Engineering, University of Málaga | |
| 3. | Juan Miguel Morales
|
| Applied Mathematics, University of Málaga |
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.
Keywords
- Programming, Mixed-Integer
- Machine Learning
- Combinatorial Optimization
Status: accepted
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