Heuristic Simulated Annealing Genetic Algorithm for Traveling Salesman Problem

Traveling Salesman Problem (TSP) is a kind of hard problem in the mathematic field. It is very hard to solve using deterministic algorithms. So it often resorts to heuristic stochastic search algorithms. In this paper, a Heuristic Simulated Annealing Genetic Algorithm (HSAGA) is presented to solve TSP problem, in which Genetic Algorithm (GA) functions as global search strategy while the designed Heuristic Simulated Annealing (HSA) algorithm acts as local search strategy applied on partial optimal solutions at each iteration. The function of HSA is to enhance the search effectiveness over the solution space and to avoid getting stuck into local optimal trap. Simulation results demonstrate that the effectiveness of the presented algorithm.