Optimization of Adaptive Genetic Algorithm Parameters in Traveling Salesman Problem

The TSP problem is one where a seller visits multiple destinations at the same time and they are only allowed to visit once. purpose of this shorten shortest distance, thereby minimizing cost. There various methods solve problem, including greedy algorithm, brute force hill climbing method, ant genetic algorithm. Each process in algorithm affected by several parameters, population size, maximum generation, crossover rate, mutation rate. study apply algorithms traveling salesman optimization, calculate influence chromosome number, rate on optimal range for effect adaptive parameters results. Based results obtained from research testing, four positively correlated with fitness while negatively execution performance each parameter applied provides more than static parameters. that together give results, both which reaches 1.0% 38.7%.