Open AccessNoise‐enhanced quantum annealing approach and its application in plug‐in hybrid electric vehicle charging optimization
Author(s) -
Xin Gang,
Wang Peng,
Jiao Yuwei
Publication year - 2021
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12112
Subject(s) - simulated annealing , quantum annealing , annealing (glass) , quantum , adaptive simulated annealing , electric vehicle , noise (video) , computer science , algorithm , mathematical optimization , electronic engineering , control theory (sociology) , mathematics , materials science , engineering , quantum computer , physics , quantum mechanics , artificial intelligence , power (physics) , image (mathematics) , composite material , control (management)
A noise‐enhanced quantum annealing algorithm is proposed for an efficient annealing process to obtain the optimal solution. Simultaneous multiple noises are introduced as the kinetic energy term into the Schrödinger equation, which effectively reduces the probability of the algorithm falling into a local optimum by the parallel annealing process. The experimental results on the numerical optimisation problem and a real‐world plug‐in hybrid electric vehicles charging problem show that the proposed scheme is very competitive.