An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products

Improved supply chain optimization strategies can play a major role in addressing global food security and safety years to come. In particular, tighter regulations, changing consumer quality requirements more stringent market competition call upon integrated decision-making frameworks that explicitly consider product control. This effort requires metrics of accurately reflect physico-chemical properties, as well purchasing preferences. However, critical challenge linked embedding the complex dynamics evolution time within models is large-scale nature ensuing problems, which are computationally intractable even for moderate-size, single-item systems. present work, we introduce efficient optimal production distribution planning framework perishable products having multiple attributes evolve function environmental conditions during shipment storage. We also propose model reduction strategy decomposition enhance scalability our approach. perform extensive numerical simulations using different network instances validate theoretical findings, demonstrate advantages proposed management scheme.