Whether it’s power grids, procurement or logistics: complex optimization tasks quickly reach their limits. At Quicopt, researchers from Forschungszentrum Jülich are developing quantum-inspired software for this purpose that runs on conventional hardware and can reduce costs for customers by up to a factor of ten.
Many industrial and economic processes rely on complex optimization tasks. This applies, for example, to power grids with millions of decentralized installations, to production planning or to demanding procurement processes. Simulations and forecasts often take too long to enable the best decision to be made in real time.
This is where Quicopt comes in. The project run by the Institute for Quantum Computing Analytics (PGI-12) at Forschungszentrum Jülich is developing quantum-inspired optimization software that utilizes the logic of quantum algorithms but runs on classical digital hardware. This should make it possible to solve complex problems more quickly and without the need for time-consuming model adjustments. Common interfaces such as Python and MATLAB are supported.
One potential area of application is so-called smart sourcing. In procurement, companies often have to find the best combination from numerous suppliers, component variants, volume discounts and shipping terms. Quicopt automates these decisions, taking into account real-world constraints such as minimum order quantities, supplier capacities or price scales.
The aim: better decisions in less time. Customers could thus significantly reduce their costs, whilst maintaining full visibility of the decisions made.
Potential areas of application range from the energy industry and the financial sector to AI, manufacturing and logistics. In this way, Quicopt aims to help solve complex optimisation problems in a practical and cost-effective manner.
Further information: https://quicopt.github.io/index.html
Contact: Tim Bode, tim@quicopt.com
