What forms of optimization are supported by Rayica and Optica 3?
Rayica and Optica 3 support all of the popular minimization algorithms. These include both constrained and unconstrained methods of minimization. Methods for constrained minimization include: the differential-evolution genetic algorithm, simulated annealing, random search, and the Nelder-Mead simplex algorithm. In addition, Rayica and Optica 3 also support the following unconstrained minimization methods: Newton, Quasi-Newton, Gauss-Newton, and principle axis (also known as Brent’s method). In addition to Rayica’s ray-trace models of optical systems and numeric optimization, Optica 3 supports symbolic models of optical systems and analytic optimization based on methods of calculus for minimization. In particular, Optica’s symbolic modelling abilities enable truely globally optimal solutions to be determined. With the help of the new dynamic work environment of Mathematica 6, managing your optimization problems in Optica 3 is now easier than ever before.
