decision - making optimization

Objective : This study addresses the fabless manufacturing business model's increasing relevance and complexity of decision-making. The primary aim is to develop and evaluate a simulation model for analyzing competitive strategies and optimizing managerial decisions in fabless supply chains.  Methodology: An agent-based simulation approach was employed to model interactions between fabless companies and manufacturing factories. The decision-making process for manufacturing partners was based on three key criteria: quality, cost, and availability. The simulation was implemented using AnyLogic software and analyzed under competitive and non-competitive market scenarios. Validation was conducted using real-world data to ensure model accuracy and applicability. Results : The study reveals that the weighting of criteria—quality, cost, and availability—significantly affects company performance in fabless manufacturing supply chains. Companies prioritizing quality tend to gain long-term advantages, while those focusing on cost may achieve short-term profits but struggle with sustainability. Competition complicates the balance of these criteria, leading to increased system-wide costs. These findings emphasize the need for nuanced strategies in dynamic markets. Conclusion : The developed simulation model offers a robust quantitative framework for analyzing and optimizing decision-making in fabless manufacturing supply chains. It is a valuable decision-support tool for managers, enabling them to adopt optimal strategies that reduce costs, enhance product quality, and improve customer satisfaction in dynamic and competitive market conditions.