@inproceedings{c543657e23f745f0b5b7ba1a16c0c36e,

title = "Solving NP-hard Problems with Quantum Annealing",

abstract = "Quadratic unconstrained binary optimization (QUBO) formulas of quantum annealing (QA) algorithms are classified into four categories. QA algorithms using different QUBO formulas solve specific NP-hard problems as examples of the classification. The NP-hard problems solved are the subset sum, the vertex cover, the graph coloring, and the traveling salesperson problems. The QA algorithms are compared with their classical counterparts in terms of the quality of the solution and the time to the solution. Based on the comparison results, observations and suggestions are given for each QUBO formula category, so that proper actions can be adopted to improve the performance of QA algorithms. Compared with classical algorithms, QA algorithms are competitive in the current noisy intermediate-scale quantum (NISQ) era and beyond.",

keywords = "NP-hard problem, noisy intermediate-scale quantum, quadratic unconstrained binary optimization, quantum annealing, quantum computer, smart manufacturing",

author = "Jiang, {Jehn Ruey} and Chu, {Chun Wei}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th IEEE Eurasia Conference on IoT, Communication and Engineering, ECICE 2022 ; Conference date: 28-10-2022 Through 30-10-2022",

year = "2022",

doi = "10.1109/ECICE55674.2022.10042862",

language = "???core.languages.en_GB???",

series = "Proceedings of the 4th IEEE Eurasia Conference on IoT, Communication and Engineering 2022, ECICE 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "406--411",

editor = "Teen-Hang Meen",

booktitle = "Proceedings of the 4th IEEE Eurasia Conference on IoT, Communication and Engineering 2022, ECICE 2022",

}