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Solve non-linear problems with a guarantee of global optimality

 

We solve optimization problems that are unsolvable using conventional optimization technology.

Octeract's optimization software guarantees that the best (global) solution to large-scale MINLP problems will always be located.

What is wrong with current optimization methods?

Stochastic methods (here PSO) never guarantee convergence to the global solution

 Multistart methods don't provide this guarantee either, and the number of starting points to achieve a good resolution increases exponentially with the number of dimensions

Multistart methods don't provide this guarantee either, and the number of starting points to achieve a good resolution increases exponentially with the number of dimensions

Modern non-linear methods can never provide a guarantee of global optimality. Considering that optimization is used to find solutions to multi-billion dollar problems, it is important to find the best possible solution every time.

How is Octeract technology different?
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Octeract software is powered by deterministic global optimization methods, which can uniquely provide this guarantee.

Although powerful, these methods have always been too slow to solve large-scale problems because it was not known how to exploit parallel hardware.

Octeract's proprietary technology breaks through this barrier by enabling the user to invest additional computational resources to solve an optimization problem much more quickly, and still retain the guarantee of finding the, extremely valuable, best solution.

Dr. Nikos Kazazakis

CEO

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Nikos has a combined 10 years of academic and industrial experience within the field of mathematical optimization and spent 5 years (PhD and postdoc) researching the field of Deterministic Global Optimization (DGO) at Imperial College London where he invented and implemented the world's first and only known algorithms on efficiently parallelising DGO methods.

 

Dr. Gabriel Lau

CTO

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Gabriel did his PhD in molecular physics at Imperial College London and has published several papers on the development of new computational techniques and mathematical methods within the fields of statistical mechanics and molecular modelling. Coming from a physics and fintech background, he has extensive experience in applying numerical algorithms and problem solving to important real-life problems as well as the development of massively parallel software.

 

Professor Claire Adjiman

Advisor

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Claire is a professor in the chemical engineering department at Imperial College London and a world-leading expert in the field of deterministic global optimization. She is also the director of the Centre for Process Systems Engineering, a multi-institutional research centre of world-class departments, that has industrial links with some of the largest oil & gas companies. In recognition of her achievements, she was recently made fellow of the royal academy of engineers.