Integrating Deep Learning Demand Forecasting with Multi-Objective Optimization for Circular Coffee Supply Chains: A Data-Driven Framework for Cost, Emissions, and Freshness Management
arXiv:2606.08314v1 Announce Type: new Abstract: The coffee supply chain is one of the most complex agri-food networks, marked by geographically dispersed production, multi-tier coordination, and high sensitivity to quality and freshness. While sustainability and digitalization have gained attention, demand forecasting, optimization, and traceability are often treated separately. This study presents a two-phase integrated framework. First, a hybrid CNN-LSTM model is used for demand forecasting. On the public Coffee Chain Sales dataset with chronological 70/15/15 splitting, the model achieves MA
The increasing complexity of global supply chains and growing pressure for sustainability are driving the immediate need for advanced, integrated solutions.
This development highlights how AI, particularly deep learning, is moving beyond theoretical applications to offer concrete, data-driven solutions for real-world supply chain challenges like waste reduction and efficiency.
Supply chain management is shifting towards more predictive, optimized, and integrated systems that can better address both economic and environmental objectives.
- · Logistics and supply chain tech companies
- · Food and beverage industry
- · AI/ML model developers
- · Sustainability consultancies
- · Traditional supply chain operators
- · Companies with high waste footprints
- · Inefficient agricultural producers
Improved efficiency and reduced waste in agricultural supply chains, leading to cost savings and better resource utilization.
Increased adoption of AI and multi-objective optimization across other complex agri-food and industrial supply chains, setting new industry standards.
Potential for a global shift towards more resilient, environmentally conscious, and data-driven supply chain ecosystems, impacting trade policies and international standards.
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Read at arXiv cs.AI