Voltage control in power systems can be accomplished by switching off some transmission lines and transferring their loading to the remaining lines. This is normally done during high voltage situations caused by low demand. By so doing, the lines remaining in service will operate above their surge impedance loading thereby consuming reactive power and hence lowering voltage to desired levels. While this operational methodology could be effective, it may introduce or sustain small signal instability, manifested as low frequency oscillations (LFO), which when not adequately damped, can endanger system security and lead to widespread outages in case of disturbances. This paper has evaluated six different multi-objective evolutionary algorithms (MOEAs) that can be used to optimize transmission line switching to concurrently improve small signal stability (SSS) during voltage control. By eigenvalue analysis, the algorithms were tested on the IEEE-30 and IEEE-118 bus models and the results indicate an improvement in SSS. Among the tested algorithms, multi-objective particle swarm optimizer with crowding distance (MOPSO-CD) was found to converge fastest, while competitive mechanism based multi-objective particle swarm optimizer (CMOPSO) yielded better results at moderate convergence rates.