A Hybrid Simulated Annealing Algorithm for Travelling Salesman Problem with Three Neighbor Generation Structures

Travelling salesman problem (TSP) has been considered as one of the most complicated problems. The problem is NP-Hard and practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. The aim of this study is to presents a hybrid method using tabu search and simulated annealing technique to solve TSP called hybrid simulation annealing (HSA). The proposed HSA algorithm incorporates three neighborhood structures, called swap, insertion and reversion, to explore different possibilities of neighbor solution. This proposed HSA not only prevents revisiting the solution but also maintains the stochastic nature. Finally, the performance of the proposed HSA is examined against tabu search and simulation annealing technique, and the preliminary results indicate that the HSA is capable of solving real-world problems, efficiently.