A quantum-inspired tensor network method for constrained combinatorial optimization problems [article]

Tianyi Hao and Xuxin Huang and Chunjing Jia and Cheng Peng
2022 arXiv   pre-print
Combinatorial optimization is of general interest for both theoretical study and real-world applications. Fast-developing quantum algorithms provide a different perspective on solving combinatorial optimization problems. In this paper, we propose a quantum inspired algorithm for general locally constrained combinatorial optimization problems by encoding the constraints directly into a tensor network state. The optimal solution can be efficiently solved by borrowing the imaginary time evolution
more » ... rom a quantum many-body system. We demonstrate our algorithm with the open-pit mining problem numerically. Our computational results show the effectiveness of this construction and potential applications in further studies for general combinatorial optimization problems.
arXiv:2203.15246v1 fatcat:y7iglyelvvde5hgupub4pezywy