Constrained network models describe a wide variety of real-world applications ranging from production, inventory, and distribution problems to financial applications. These problems can be solved with ...

PROC NETFLOW solves network problems that can have side constraints. Certain algebraic features of networks are exploited by a specialized version of the Simplex method so that solution times are ...

Simplex optimization is one of the simplest algorithms available to train a neural network. Understanding how simplex optimization works, and how it compares to the more commonly used back-propagation ...