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Predictive Logistics Management of Car Sales Based on Machine Learning Algorithm for Supply Chain
Conference proceeding

Predictive Logistics Management of Car Sales Based on Machine Learning Algorithm for Supply Chain

Pranav Pandurang Gaikwad, Esam Alhomaidi, Shishir Gupta, Anvesh Perada, Mangesh Purushottam Dande and E. Muthukumar
2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES), pp 1-5
15 Nov 2024
DOI: https://doi.org/10.1109/IC3TES62412.2024.10877436

Abstract

and Distribution Processes Automobiles Car Sales and Machine Learning Algorithms Costs Customer satisfaction Demand Forecasting Inventory Management Machine learning algorithms Organizations Prediction algorithms Predictive Logistics Management Predictive models Supply Chain Optimization Supply chains Machine Learning
Machine learning algorithms are implemented in predictive logistics management to optimize the supply chain for vehicle sales. These algorithms are capable of predicting future demand, managing inventory levels, and optimizing distribution procedures by analyzing historical data, prevailing market patterns, and additional external factors. Organizations may enhance customer satisfaction, minimize lead times, and maintain appropriate inventory levels by implementing predictive models. This approach not only improves the overall efficacy of the supply chain, but it also decreases the costs associated with inventory shortages and excess inventory. The integration of machine learning (ML) into logistics management (LM) offers a data-driven solution to the complex and ever-changing supply chain scenarios.

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