A Slow-Wave Structure Optimization with Variable Helix Section Length in STWT Based on CI-NMCSO Algorithm

摘要： A novel slow-wave structure optimization method on Chaos-improved Normal mutation cat swarm optimization (CI-NMCSO) algorithm is proposed. Under the variable helix section length in STWT, the CI-NMCSO combined with 1D CHRISTINE code is used to calculate the best set of pitch distribution and section length with the objective function of electron beam efficiency improvement. Quantum particle swarm optimization (QPSO) and Cauchy mutated cat swarm optimization (CMCSO) algorithms are applied to make performance comparison. Experimental results show that the beam efficiency has been increased by CI-NMCSO from rated value 30% to 45.3%, and the values using CMCSO and QPSO are 41.8% and 36.5%, respectively, the convergence speed of CI-NMCSO is the fastest, only 16 iterations, while CMCSO and QPSO take 19 and 23 iterations, so the performance of CI-NMCSO is better than CMCSO and QPSO on both optimization precision and calculation speed in terms of slow-wave structure optimization, and is also superior to that with equal section length when the helix section length is variable.