Here's how we'll proceed:
Posted: Thu Feb 20, 2025 7:06 am
we set the required number of orders per year, take into account important business events and macroeconomic factors in order to set values for dummy variables for the forecast period, as well as upper limits for new clients for each month;
we enter data on new clients for each month;
Based on this data, the system makes a forecast for the total number of orders macedonia mobile database for the year;
We repeat steps 2 and 3 until we find the optimal solution, where the difference between the forecast and the required number of orders is minimal.
The process of finding the optimal number of new clients by month can be visualized as follows:
Formally, the optimization problem can be described as follows:
Where b is the required number of orders per year, xn is the number of new customers in month n, an is the upper limit for the number of new customers in month n.
To solve the optimization problem, we use the SLSQP (Sequential Least Squares Programming) method from the SciPy library.
we enter data on new clients for each month;
Based on this data, the system makes a forecast for the total number of orders macedonia mobile database for the year;
We repeat steps 2 and 3 until we find the optimal solution, where the difference between the forecast and the required number of orders is minimal.
The process of finding the optimal number of new clients by month can be visualized as follows:
Formally, the optimization problem can be described as follows:
Where b is the required number of orders per year, xn is the number of new customers in month n, an is the upper limit for the number of new customers in month n.
To solve the optimization problem, we use the SLSQP (Sequential Least Squares Programming) method from the SciPy library.