<![CDATA[Modern supply chains are increasingly unpredictable and interconnected, making traditional forecasting and optimization models inadequate. This paper introduces a novel framework inspired by quantum mechanics to better capture the uncertainty and complexity of supply chains. By modeling inventory, demand, and risk as quantum-like entities called sharons, the framework treats these components as both particles (discrete units) and waves (continuous flows). The resulting Sharon wave function represents all possible supply chain states and evolves over time using principles like superposition, interference, and uncertainty. We define quantum-inspired operators to extract insights into demand, inventory, cost, and risk. Through mathematical modeling and real-world data, we demonstrate how this approach improves forecasting accuracy and enables dynamic strategy optimization. This framework offers a new lens to understand and manage supply chain behavior under uncertainty and aligns well with emerging quantum computing technologies.]]>
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