A5019309342- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Transportation and Mobility Innovations
- Transportation Planning and Optimization
- Smart Parking Systems Research
- Optimization and Search Problems
- Machine Learning and Algorithms
- Optimization and Packing Problems
- Human Mobility and Location-Based Analysis
- Cloud Computing and Resource Management
- Radiation Effects in Electronics
- Parallel Computing and Optimization Techniques
- Constraint Satisfaction and Optimization
- Sharing Economy and Platforms
BMW Group (Germany)
2024
BMW (Germany)
2019-2023
Technical University of Munich
2021
Abstract Quantum computing promises to overcome computational limitations with better and faster solutions for optimization, simulation, machine learning problems. Europe Germany are in the process of successfully establishing research funding programs objective advance technology’s ecosystem industrialization, thereby ensuring digital sovereignty, security, competitiveness. Such an comprises hardware/software solution providers, system integrators, users from institutions, start-ups,...
Optimization problems are ubiquitous in various industrial settings, and multi-knapsack optimization is one recurrent task faced daily by several industries. The advent of quantum computing has opened a new paradigm for computationally intensive tasks, with promises delivering better faster solutions specific classes problems. This work presents comprehensive study approaches problems, investigating some the most prominent state-of-the-art algorithms using different software hardware tools....
On-Demand Mobility is an increasingly popular concept especially in urban areas, which has the potential to reduce congestion and space needed by privately owned vehicles due shared car fleets. To avoid a decline of flexibility convenience for customers minimize costs service provider, fleet management algorithm matches requests order quickly find reliable time efficient solution whole system. The focus this work introduce new approach solutions periodically using Tabu Search metaheuristic,...
In this paper, we show the design and implementation of a quantum algorithm for industrial shift scheduling (QISS), which uses Grover's adaptive search to tackle common important class valuable, real-world combinatorial optimization problems. We give an explicit circuit construction oracle, incorporating multiple constraints present in problem, detail corresponding logical-level resource requirements. Further, simulate application QISS specific small-scale problem instances corroborate...
In this paper, we use open-source tools to perform quantum resource estimation assess the requirements for industry-relevant computation. Our analysis uses problem of industrial shift scheduling in manufacturing and Quantum Industrial Shift Scheduling algorithm. We base our figures merit on current technology, as well theoretical high-fidelity scenarios superconducting qubit platforms. find that execution time gate measurement operations determines overall computational runtime more strongly...
Quantum computing could impact various industries, with the automotive industry many computational challenges, from optimizing supply chains and manufacturing to vehicle engineering, being particularly promising. This chapter investigates state-of-the-art quantum algorithms enhance efficiency, accuracy, scalability across value chain. We explore recent advances in optimization, machine learning, numerical chemistry simulations, highlighting their potential limitations. identify discuss key...