Quantum computers open up new possibilities for faster and more efficient solutions to real-world, large-scale optimization problems that currently pose a challenge for classical computer systems. One such problem is searching very large neighborhoods, with an exponential number of elements, in local search algorithms for solving NP-hard problems. Currently, the only barrier to the effective use of quantum computers in optimization is the limited number of available qubits. Therefore, the main challenge today, given the limited number of qubits, is to formulate the problem to be solved in a form that minimizes the number of variables and, consequently, the number of necessary qubits. To meet these expectations, authors propose a new solution representation used to generate neighborhoods with an exponential number of elements.

In this article a quantum-ready formulation was used for solving the equal demand capacitated vehicle routing problem on a superconducting quantum computer.

This paper addresses the NP-hard problem of scheduling jobs on two machines in Flexible Manufacturing Systems (FMS), supported by Autonomous Artificial Intelligence (AAI), with the goal of minimizing the total weighted number of tardy jobs.

The efficient management of complex production systems is a challenge in today’s logistics. In the field of intelligent and sustainable logistics, the optimization of production batches, especially in the context of a rapidly changing product range, requires fast and precise com- putational solutions. This paper explores the potential of quantum computers for solving these problems.

Data-driven approaches become more and more attractive in building performance analysis including performance assessment of heat, ventilation, and air conditioning (HVAC) systems. Their popularity is associated with the increasing availability of large amounts of high-quality building-related measurement data. The study is focused on a data-driven approach that enables post-operation evaluation of AC performance based on indoor air monitoring. It allows for the identification of the classifying solution which recognizes the monitoring data that is representative of thermal conditions during AC operation.

Raport można pobrać na stronie: https://report.startupwroclaw.pl. Jest to kompleksowa analiza dynamicznego krajobrazu innowacji w regionie Dolnego Śląska. Raport ukazuje m.in. potencjał infrastruktury badawczej Politechniki Wrocławskiej oraz rozwój technologii AI i obliczeń kwantowych na uczelni, co dzieje się między innymi dzięki działaniom WCSS. Jeden z rozdziałów raportu przedstawia Wrocław jako miasto, które oferuje unikalny ekosystem obliczeniowy dostępny w WCSS, łączący światowej klasy klasyczne superkomputery z technologią kwantową (str. 142-143 publikacji).

W raporcie PRACE 2019 znalazły się informacje na temat rozwoju inicjatyw lokalnych w ramach przedsięwzięcia EuroHPC Joint Undertaking, na którym opiera się działalność PRACE. Dokument przedstawia również wyzwania, z jakimi mierzą się jednostki badawcze posiadające infrastrukturę dużych mocy obliczeniowych.