Abstract
Supply chain optimization is crucial for firms to boost efficiency and competitiveness amidst increasing complexity and risks in global markets. This study provides light into the optimization of a global supply chain network using genetic algorithms, concentrated on avoiding disruptions and decreasing total supply chain costs. The main objectives comprise decreasing total supply chain costs, managing disruptions in product quantity and quality, and optimizing operating parameters and features. The study employs genetic algorithms for optimization, explaining the approach and providing final interpretations to boost supply chain efficiency and resilience against disturbances.
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