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  4. Harnessing Inferior Solutions for Superior Outcomes: Obtaining Robust Solutions from Quantum Algorithms
 
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2024
Conference Paper
Title

Harnessing Inferior Solutions for Superior Outcomes: Obtaining Robust Solutions from Quantum Algorithms

Abstract
In the rapidly advancing domain of quantum optimization, the confluence of quantum algorithms such as Quantum Annealing (QA) and the Quantum Approximate Optimization Algorithm (QAOA) with robust optimization methodologies presents a cutting-edge frontier. Although it seems natural to apply quantum algorithms when facing uncertainty, this has barely been approached.
In this paper we adapt the aforementioned quantum optimization techniques to tackle robust optimization problems. By leveraging the inherent stochasticity of quantum annealing and adjusting the parameters and evaluation functions within QAOA, we present two innovative methods for obtaining robust optimal solutions. These heuristics are applied on two use cases within the energy sector: the unit commitment problem, which is central to the scheduling of power plant operations, and the optimization of charging electric vehicles including electricity from photovoltaic to minimize costs. These examples highlight not only the potential of quantum optimization methods to enhance decision-making in energy management but also the practical relevance of the young field of quantum computing in general. Through careful adaptation of quantum algorithms, we lay the foundation for exploring ways to achieve more reliable and efficient solutions in complex optimization scenarios that occur in the real-world.
Author(s)
Halffmann, Pascal
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
Trebing, Michael
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
Lenk, Steve
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Mainwork
GECCO 2024 Companion, Genetic and Evolutionary Computation Conference Companion. Proceedings  
Conference
Genetic and Evolutionary Computation Conference 2024  
Open Access
DOI
10.1145/3638530.3664160
Additional full text version
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Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM  
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