A New Heuristic Algorithm Based on Nearby Measures for Shortest Path Calculation

Path planning is one of the key performance indexes to realize intelligent and efficient robot work. For improving the mobile efficiency of the robot, the Nearby Measures & Simulated Annealing (N-SA) algorithm model is proposed in this paper to solve the TSP. By combining the nearby measures with the traditional simulated annealing (SA) algorithm, the convergence rate of the original SA algorithm can be accelerated. At the same time, the solution generated by SA can be optimized by using the nearby measures to solve the path crossing problem. In the experiment, TSPLIB data set is used for verification, which can make the mass of the solution converge more than 95% quickly. The computational model has the characteristics of fast speed, small amount of computation and strong universality, which can provide certain research value for the efficient movement of robots.