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The ~Million Variable Universal Optimization Solver

Discrete, Binary, Mixed-Integer
[Un]Constrained
Multi-Objective
Stochastic / Robust
[Non]Linear
Combinatorial

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Why did we succeed where everyone else failed?

Because 90% of the people in the world use Gradient based methods for solving optimization problems, which is useless for NP-Hard, Non-Linear Problems, which are pretty much everything we want to solve.

Because the other 10% use what they call Gradient "Free" (???) Methods. They dont calculate gradients but rather they use differences. This fancy terminology scheme is also absolutely useless.

Because we built our solvers using Gradient "Agnostic" Methods. And they can solve absolutely any optimization problem anyone can even conceive.

Universal Optimization Solver

"Optimization is now a solved problem"

Which problems can we solve using our solver?

Pretty much any optimization problem you can think of. With arbitrary constraints, objectives and variable types & domains.

Is the solver classical or quantum based?

This particular solver is completely classical. Though it is often used to help with Variational Quantum Algorithms in the role of the classical optimizer driving the Quantum Circuits.

Can it really support a million+ variables?

In the pure software mode it supports lesser. But in the production environment it can. Because the production environment uses HPC clusters with custom built hardware accelerators.

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Universal Optimization Solver

Any Variable Type
Any Domain
Arbitrary Constraints

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