Mathematical optimization is a field dedicated to finding the optimal solution for a specific problem based on a given set of constraints and conditions. It is used to make efficient and effective decisions in situations where resources are limited, requiring the maximization of benefits or minimization of costs.

There are various approaches and methods for solving optimization problems, and the choice of the appropriate method depends on the type of problem and the nature of the constraints involved. Among the most common methods we use at Belerofontech are the creation of optimization models using integer linear programming (MILP) techniques along with forecasting techniques based on time series analysis and regression models.

At Belerofontech, we collaborate with Gurobi, the leading solver for high-performance mathematical optimization, used to solve complex optimization problems.

Mathematical optimization has applications in a wide range of fields, such as engineering, economics, business management, and data science, among others. At Belerofontech, we apply mathematical optimization in projects such as:

• Optimization of operational processes
• Production optimization
• MRP optimization
• Planning optimization
• Distribution route optimization
• Replenishment optimization
• Cost optimization
• Purchasing process optimization