GPU-Powered Simulation and Optimization of AI-Driven Supply Chains: Integrating Business Analytics, Generative Design, and Robotics for Enhanced Efficiency and Resilience

EasyChair Preprint 14496

Abstract

The rapid evolution of global supply chains demands innovative approaches to enhance efficiency, resilience, and sustainability. This paper explores the integration of GPU-powered simulations and optimization techniques within AI-driven supply chains. By leveraging advanced business analytics, generative design, and robotics, we propose a framework that accelerates decision-making processes and optimizes supply chain performance. The study focuses on the application of GPU acceleration to simulate complex supply chain scenarios in real-time, enabling the rapid identification of bottlenecks and the development of adaptive strategies. The incorporation of generative design principles allows for the automated generation of optimal supply chain configurations, while robotics integration enhances operational efficiency and flexibility. Through case studies, we demonstrate the significant improvements in supply chain resilience and efficiency, highlighting the transformative potential of GPU-accelerated AI technologies in modern supply chain management.

Keyphrases: AI-driven supply chains, Business Analytics, GPU acceleration, Resilience, Robotics integration, Supply Chain Optimization, adaptive strategies, generative design, operational efficiency, real-time simulation

@booklet{EasyChair:14496,
  author    = {Abi Cit},
  title     = {GPU-Powered Simulation and Optimization of AI-Driven Supply Chains: Integrating Business Analytics, Generative Design, and Robotics for Enhanced Efficiency and Resilience},
  howpublished = {EasyChair Preprint 14496},
  year      = {EasyChair, 2024}}