Process Optimization

Mathematical optimization involves minimizing (or maximizing) some cost function while satisfying a set of binding constraints. Almost any process can benefit from the application of optimization technology to assist in decision-making and policy.

I.Q. Technologies, Ltd. has a team of consultants that can help your business to optimize its processes by employing two different technologies: Linear Programming (LP) and Constraint Programming (CP).

• Linear Programming - Linear Programming is the most common optimization technique. It can be used when the process to be optimized can be represented using linear equations. This is often the case with many manufacturing and production problems. The techniques used to solve these problems guarantee an optimal solution, which can greatly cut costs of production if the problem is modeled correctly.
• Constraint Programming - Constraint programming is used to solve problems where linear programming is not sufficient for the task.

  Optimization of Patient Schedule

  This can occur if the equations that model a process are nonlinear, or if there are integer solutions. In both of these cases, linear programming is not a good choice for solving these types of problems. Constraint programming quickly solves problems where there is an objective function and a set of constraints that must be satisfied. The objective function represents the goals of the user, and the constraints are limits to what is possible. Constraint Programming allows the user a large degree of flexibility in representing these faithfully.