Table 2 Characteristics comparative analysis of the performance and the control parameters of improved optimization algorithms.

From: Multi objective optimization algorithm for hybrid quantum harmonic oscillator and its application in rotor system optimization

Improved algorithm

Control parameters

performance

CIMPSOA

Cognition factor \(c_{1}\), social factors \(c_{1}\), speed inertia weight \(w_{v}\)

Fast convergence speed, but poor repeat retention characteristics

mMQHOA

Convergence scale \(A_{c}\)

Repeatedly maintaining stable characteristics, but with slow convergence speed

IM2QHOA

Convergence scale \(A_{c}\)

Fast convergence, stable repetitive characteristics

HMGA

Convergence scale \(A_{c}\), genetic selection rate \(g_{s}\), discrete recombination rate \(d_{r}\), mutation rate \(v_{r}\), perturbation number \(R_{m}\)

Depends on perturbation parameters \(R_{m}\)