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.

In the paper author presents a new approach to solving NP-hard problems of discrete optimization adapted to the architecture of quantum processors (QPU, Quantum Processor Unit) implementing hardware quantum annealing. This approach is based on the use of the quantum annealing metaheuristic in the exact branch and bound algorithm to compute the lower and upper bounds of the objective function. To determine the lower bound, a new method of defining the Lagrange function for the dual problem (the generalized discrete knapsack problem) was used, the value of which is calculated on the QPU of a quantum machine. In turn, to determine the upper bound, we formulate an appropriate task in the form of binary quadratic programming with constraints.

Plakat przedstawiony na konferencji: International Conference on Computational Science, która odbyła się w dniach 3-5 lipca 2023 roku w Pradze.

In this paper authors propose a methodology for generating good lower bounds on the optimal value of the objective function using a quantum machine.

The PRACE 2019 report includes information on the development of local initiatives within the EuroHPC Joint Undertaking, on which PRACE is based. The document also outlines the challenges faced by research entities with high-performance computing infrastructure.