The possibility of having true global optimization for a large number of variables such as in multi-layer thin film design, has been debated for decades. A true global optimization algorithm works for a variety of different applications to find the best possible outcome for many interlinked variables. In thin film design, it can reduce the time taken to obtain optimum designs, allow designers to find solutions to unfamiliar problems, reduce manufacturing costs, and achieve goals that were previously considered impossible. While some programs claim to offer global optimization, they fail the characteristic test for a true global optimization algorithm. The test is a simple one: the user starts with an arbitrary multilayer design (more than 5 layers is a sufficient challenge) and calculates its reflectance or transmittance. Then, the user makes this reflectance or transmittance figure the target of a software optimization. A true global optimization algorithm will get back to the original design every time, while other algorithms will, most of the time, come up with different designs. A new technique promises true global optimization in a methodical manner. It means that designers will not need to repeat an optimization with a different starting guess just to verify that their result is truly optimal.