The Cutting Stock Problem (CSP) has been deeply investigated by computer science and mathematics because it has a wide field of applications in the real world, most commonly used in industrial processes such as the Architectural Aluminium, Glass, Glazing and Manufacturing Industries.
This Cutting Stock Problem (CSP) tries to find the optimal plan to assign constrained resources to satisfy a demand in the most efficient way (optimal) having a measure of that efficiency (objective function). It is a classic optimization problem, and its complete analytical solution is not trivial, it is also based on complex mathematical developments.
As previously mentioned the Cutting Stock Problem (CSP) has known analytical solutions (integer linear programming), nevertheless the analytical solution cannot always be reached to solve real problems in real time, due to the complexity of calculations involved growing exponentially with the quantity of variables (data) in the problem. Usually this known analytical solution is only applied to cases that involve small quantities of variables (small cutting requirements)
A broad bibliography on the 1D Cutting Stock Problem (CSP) can easily be found, therefore practical solvers like Optimumcut Optilib.dll use a wide variety of strategies to reach acceptable solutions for this problem.
Optimumcut have developed over the last 12 years our own commercial Cutting Stock Problem (CSP) one dimensional 1D cutting stock linear optimization algorithms Optimumcut Optilib.dll which resolve the Cutting Stock Problem (CSP) in a fast and accurate way. Our solutions calculate and display exactly how to obtain the best yield from stock lengths and re-useable off-cuts of profiles.
Subsequently with such a powerful and reliable 1d linear optimization algorithm Optimumcut Optilib.dll is compiled into all of our products ensuring maximum yield with minimum waste.
By choosing Optimumcut products, our users are safe in the knowledge they will always able to Obtain the Maximum from a Minimum®