An Improvement to the 2-Opt Heuristic Algorithm for Approximation of Optimal TSP Tour

The travelling salesman problem (TSP) is perhaps the most researched in field of Computer Science and Operations. It a known NP-hard has significant practical applications variety areas, such as logistics, planning, scheduling. Route optimisation not only improves overall profitability logistic centre but also reduces greenhouse gas emissions by minimising distance travelled. In this article, we propose simple improved heuristic algorithm named 2-Opt++, which solves symmetric TSP problems using an enhanced 2-Opt local search technique, to generate better results. As with 2-Opt, our proposed method can be applied Vehicle Routing Problem (VRP), minor modifications. We have compared technique six existing algorithms, namely ruin recreate, nearest neighbour, genetic algorithm, simulated annealing, Tabu search, ant colony optimisation. Furthermore, allow for complexity larger instances, used graph compression/candidate list that helps reducing computational time. comprehensive empirical evaluation carried out research work shows efficacy 2-Opt++ it outperforms other well-known algorithms terms error margin, execution time, time convergence.