Abstract
The efficiency of supply chains is pivotal in ensuring competitive advantage in manufacturing sectors. With the advent of globalization and heightened customer expectations, supply chain optimization has become a strategic imperative. This paper explores various optimization techniques used in manufacturing supply chains to enhance responsiveness, minimize costs, and increase operational agility. Methods such as linear programming, metaheuristics, machine learning, and simulation-based optimization are evaluated in terms of application, efficiency, and scalability. Emphasis is placed on real-time data integration and predictive analytics, which are transforming traditional supply chains into responsive digital ecosystems. The paper concludes by identifying challenges and potential research areas for future optimization models.
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