Graph Theory for Computer Science

12Fuzzy Graph Theory–Enhanced Gradient Boosting Regression with Network Flow Graphs for Effective Inventory Management Amid Shortages

K. Kalaiarasi^1,2* and N. Sindhuja¹

¹PG and Research Department of Mathematics, Cauvery College for Women (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli, Tamil Nadu, India

²D.Sc (Mathematics) Researcher, Srinivas University, Surathkal, Mangaluru, Karnataka, India

Abstract

In modern business operations, effective inventory management is paramount, especially amidst shortages or volatile demand patterns. Conventional inventory optimization methods often falter in the face of uncertainty and complex data relationships. This paper introduces a novel approach that integrates fuzzy graph theory into gradient boosting regression models to tackle these challenges. By melding the interpretability of fuzzy graph theory with the predictive prowess of gradient boosting regression, this methodology offers a robust framework for optimizing inventory management, particularly in shortage scenarios. Moreover, the implementation encompasses in Python programming languages, ensuring adaptability and computational efficiency for practical deployment. Through empirical assessments on diverse datasets, the efficacy and superiority of the proposed approach over existing methods are demonstrated. Additionally, the utilization of network flow graphs aids in visualizing goods movement within the inventory network, thereby facilitating insights into ...