Synera add-in · Optimization
Raphos Optimizer
Single- and multi-objective optimization for Synera workflows — from gradient methods to metaheuristics.
Raphos Optimizer turns a Synera workflow into a search problem you can solve automatically. Expose a few inputs, define one or more objectives and any constraints, and the optimizer drives the workflow towards better designs — exploring the design space far more thoroughly than a human tweaking sliders ever could.
It carries across the optimization know-how Raphos uses in its consulting work: the right algorithm for the shape of the problem, robust handling of constraints, and results you can trust.
Algorithms for the problem you actually have
Not every problem wants the same solver. Raphos Optimizer offers a range of strategies so the method fits the problem rather than the other way round.
- Gradient and stochastic-gradient descent for smooth, differentiable objectives.
- Genetic algorithms and simulated annealing for rugged, discrete or non-differentiable design spaces.
- Multi-objective optimization that returns a Pareto front of trade-offs instead of a single answer.
- Constraint handling so solutions stay feasible and buildable.
Optimization as a workflow step
Because it runs inside Synera, the optimizer can drive a complete pipeline: generate geometry, evaluate it (in Synera or via a connected solver such as SimScale), score it and iterate — all without leaving the canvas. That makes it straightforward to optimize against real engineering metrics like mass, utilisation, stiffness or flow performance.
More in Synera Add-ins
Related work.
Interested in Raphos Optimizer?
Tell us about your problem — we’ll tell you how we’d approach it.