To enhance the performance of genetic algorithms, various approaches have been developed. One promising approach is to improve the quality of the initial population. A genetic algorithm can commence with either a cold or warm start. A cold start refers to a random initialization from scratch, whereas a warm start leverages existing knowledge about desired candidates for targeted initialization.