Reinforced Hybrid Genetic Algorithm for the Traveling Salesman Problem

Given a set of cities with certain locations, the Traveling Salesman Problem (TSP) is to find the shortest Hamiltonian route, along which a salesman travels from a city to visit all the cities exactly once and finally returns to the starting city. The TSP is one of the most famous and well-studied NP-hard combinatorial optimization problems, which is very easy to understand but very difficult to solve optimally or near-optimally. Over the years, TSP has become a touchstone for the algorithm design. Typical methods for solving the TSP are mainly exact algorithms, approximation algorithms and heuristics. The exact algorithms may be prohibitive for large instances and the approximation algorithms may suffer from weak optimal guarantees or empirical performance (Khalil et al. 2017). Heuristics are known to be the most efficient and effective approaches for solving the TSP.