ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses.

ABSTRACT: With the rapid expansion of global e-commerce, effectively managing supply chains and optimizing transportation costs has become a key challenge for businesses. This research proposed a new framework named Intelligent Supply Chain Cost Optimization (ISCCO). ISCCO integrates deep learning with advanced optimization algorithms. It focuses on minimizing transportation costs by accurately predicting customer behavior and dynamically allocating goods. ISCCO significantly enhanced supply chain efficiency by implementing an innovative customer segmentation system. This system combines autoencoders with random forests to categorize customers based on their sensitivity to discounts and likelihood of cancellations. Additionally, ISCCO optimized goods allocation using a genetic algorithm enhanced int

SUBMITTER: Li Y 

PROVIDER: S-EPMC11784774 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature