In an increasingly complex and uncertain business environment, decision makers require robust strategies for supply chain aggregate production planning that account for the interdependencies and coordination across multiple echelons of the supply chain network. Traditional approaches often...

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply...

This study presents a class-based approach developed to evaluate the financial performance of companies that have undergone public listing on the stock market. By employing both statistical analysis and machine learning methods, the models consider two important determinants, which are the...