About Us

Discover Better Designs, Faster

About Red Cedar Technology
Red Cedar Technology helps companies discover better designs, faster.  Our optimization software and services assist our clients in producing innovative solutions, reducing product development time and risks, and meeting or exceeding customer expectations. Product teams worldwide use our expertise to design safer cars, engineer life-saving biomedical devices, and develop innovative structures for air travel and space exploration, among other groundbreaking applications. 

Red Cedar Technology is a wholly-owned subsidiary of CD-adapco, the largest privately-held CFD-focused provider of computer aided engineering software & services. We have our headquarters in East Lansing, Michigan, and software distributors throughout the world. We offer optimization services and software to our customers and clients based on our core values — unbridled innovation, uncompromising integrity, and quality in everything we do.

Modern Principles of Design Optimization
Our view of optimization is free of the constraints imposed by previous technology, because it is based on a set of new principles that allow a more natural flow of thought and effort. These eight principles are the foundation of everything we do in software development, consulting services and training at Red Cedar Technology:
Principle 1:  Start with a good concept, not necessarily a good design.
Let the optimizer do the work of searching for good designs.

Principle 2:  Optimize early and often.
Not just at the end of the design cycle or after all other means have been exhausted.

Principle 3:  Define the design problem you need to solve.
Not the one that can be solved by a certain optimization strategy.

Principle 4:  Optimize the system interactions.
Not just the components.

Principle 5:  Let the optimization algorithm figure out how to search the design space.
There's often no way to guess ahead of time which search method and tuning parameters will work best.

Principle 6:  Don't perform optimization using models of your models.
Response surface or surrogate models often increase effort and error.

Principle 7:  Be an engaged participant in the optimization search.
Leverage your knowledge and intuition during a collaborative search process.

Principle 8:  Care about the sensitivities of your final design.
Not those of your initial guess, which often have no bearing on the final design.