Objectives: The objective is to identify weakest buses using L-index method and to reduce the maximum value of L-index using Genetic Algorithm so as to maintain the voltage profile. Methods/Statistical Analysis: Among the various existing voltage stability indices, L-index is implemented in this paper since it involves simple calculation with high accuracy and reliability. Hence on identifying buses with maximum L-index, it becomes essential to minimize the L-index to maintain the system stability. Genetic Algorithm is chosen since it is faster and more accurate when implemented for power system problems in particular to optimize the voltage. Findings: The variations to be adopted for the control variables which are thus obtained for IEEE 30 bus system by using Genetic Algorithm are highly important to reduce L-index value. The voltage profile is improved better when Static Var Compensator is placed at the first weakest bus rather than the improvement in the voltage profile on employing a compensator in the next weakest buses which indicates the importance in identification of weakest buses. The significance of weakest buses are still emphasised on considering normal condition and contingency condition which shows that under contingency it is the weakest buses which is much more affected and hence driving the entire system towards voltage collapse. Application/Improvements: Hence by identifying the weakest buses using L-index and by minimizing the maximum value of L-index using Genetic Algorithm along with reactive power compensator improves the voltage profile better.