Technologies

Introducing Concurrent Gradient Analysis

Optimization of competing objectives is based on a very simple premise, first applied to economic models by Vilfredo Pareto, in the 19th century. In economics, a Pareto optimal solution is one where no individual can be made better off without another being made worse off. Since its introduction, this concept, called Pareto optimization, has been extended to many other fields. Today, the field of product design is currently one of the most prominent users of Pareto optimization for solving problems with multiple objectives.

There is not one optimal solution, but typically a range of optimal solutions. All those solutions lie on the Pareto Frontier, also called the Pareto surface. Finding solutions that lie on the Pareto Frontier, and actually driving along the Pareto Frontier is what puts Multistat products ahead of the rest. Bringing the most important technological aspects of design optimization software to the forefront with the efficiency, scalability, and accuracy of multi-objective optimization algorithms, Multistat has developed a series of proprietary algorithms utilizing a concept called Concurrent Gradient Analysis. Very simply, Concurrent Gradient Analysis extends the concept of single object Gradient Based optimization to work with multiple objectives simultaneously.

Multistat’s unique approach to design optimization allows highly dimensioned, multi-objective problems to be solved in a fraction of the time required by other methods.

Need an explanation of some terminology? – Read the Optimization Glossary