Frontiers in Physics (Jan 2023)

Quantum-inspired optimization for wavelength assignment

  • Aleksey S. Boev,
  • Sergey R. Usmanov,
  • Alexander M. Semenov,
  • Maria M. Ushakova,
  • Gleb V. Salahov,
  • Alena S. Mastiukova,
  • Evgeniy O. Kiktenko,
  • Aleksey K. Fedorov

DOI
https://doi.org/10.3389/fphy.2022.1092065
Journal volume & issue
Vol. 10

Abstract

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Problems related to wavelength assignment (WA) in optical communications networks involve allocating transmission wavelengths for known transmission paths between nodes that minimize a certain objective function, for example, the total number of wavelengths. Playing a central role in modern telecommunications, this problem belongs to NP-complete class for a general case so that obtaining optimal solutions for industry-relevant cases is exponentially hard. In this work, we propose and develop a quantum-inspired algorithm for solving the wavelength assignment problem. We propose an advanced embedding procedure to transform this problem into the quadratic unconstrained binary optimization (QUBO) form, having a improvement in the number of iterations with price-to-pay being a slight increase in the number of variables (“spins”). Then, we compare a quantum-inspired technique for solving the corresponding QUBO form against classical heuristic and industrial combinatorial solvers. The obtained numerical results indicate on an advantage of the quantum-inspired approach in a substantial number of test cases against the industrial combinatorial solver that works in the standard setting. Our results pave the way to the use of quantum-inspired algorithms for practical problems in telecommunications and open a perspective for further analysis of the use of quantum computing devices.

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