In order to give decision alternatives, the algorithm must give a satisfactory solution in a relatively short period of time

The TSP (Traveling Salesman Problem, TSP) is a typical combinatorial optimization problem, has become and will continue to be testing the new algorithm hotspot combinatorial optimization problems. In the traditional TSP problem, the city's size and the distance between cities is fixed, but in practice, the size and cost of the problem is often the vector matrix dynamic changes over time, saying such issues as dynamic TSP. In order to give managers the right decision scheme, the algorithm must be based on real-time information in a relatively short period of time given satisfactory solution. Research on such issues, not only for all types of dynamic  cubic boron nitride  optimization  synthetic diamond  a theoretical reference, but also has a wide range of practical value. As an adaptive genetic algorithm for global optimization probabilistic search algorithm, with simple and universal, robust and strong,  Abrasive grinding  and parallelism, etc., has been successfully applied to solve combinatorial optimization problems. In this paper, an improved genetic algorithm to solve TSP problems, the main research work and innovation on the TSP problems were analyzed to establish a mathematical model.