ACO-SA: ENHANCED OPTIMIZATION FOR TSP

Abstract

Traveling salesman problem (TSP) is traditional combinatorial-optimization problem and a NP-problem in operation research. Swarm intelligence (SI) algorithms be capable of efficiently achieve best tours with minimum lengths. ACO is type of probability technology use to get the optimal path in the graph. Through the analysis on the main reasons resulting in low convergence rate to overcome it simulated annealing optimization are used. In this, new hybrid ACO-SA algorithm for solving TSP depended on ACO with SA optimization technique which avoids trapping in the local-minima points. Experiments have performed using data set obtained from TSPLIB and contrast the new results of proposed method with existing methods. The results illustrate that both the average cost and number of the iteration to the best known solution of proposed method are better than existing methods.