A Data-Driven pricing Model for Distribution Systems Considering Competition

Document Type : Research Paper

Author

School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

10.22059/aie.2024.370998.1885

Abstract

In this paper, considering the significant shifts in customer preferences, the need to investigate customer behavior and incorporate competition has led to the utilization of mathematical modeling for designing this process. The proposed model aims to maximize profits in a competitive market for a distribution system including a wholesaler and multiple retailers in a multi-period and multi-product setting. The customer behavior issue is modeled through a behavior-based pricing process at the retail level, and then equilibrium values are determined using bi-level programming considering Stackelberg modeling based on an asymmetric competition. The proposed model is solved by presenting two different approaches: structural modification and data-driven learning models. In the first case, the proposed bi-level model is converted to a single-level equivalent after linearization. Then, in the latter case, the data-driven approach, an attempt is made to manage the pricing process using CLIQUE clustering method and developing a rule-based pricing system based on data extraction. Finally, in order to clarify concepts, numerical examples and sensitivity analyses are performed, and the defined examples are compared to each other, highlighting the managerial implications and future research directions.

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Advances in Industrial Engineering

Articles in Press, Accepted Manuscript
Available Online from 27 February 2024

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