Local optimization and the traveling salesman problem
Proceedings of the seventeenth international colloquium on Automata, languages and programming
ACM Computing Surveys (CSUR)
New Genetic Local Search Operators for the Traveling Salesman Problem
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Some NP-complete geometric problems
STOC '76 Proceedings of the eighth annual ACM symposium on Theory of computing
Proof verification and hardness of approximation problems
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
A hybrid heuristic for the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Toward minimal restriction of genetic encoding and crossovers for the two-dimensional Euclidean TSP
IEEE Transactions on Evolutionary Computation
A Vehicle Routing Problem Solved by Agents
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
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A new evolution strategy based on clustering and local search scheme is proposed for some kind of large-scale travelling salesman problems in this paper. First, the problem is divided into several subproblems with smaller sizes by clustering, then the optimal or the approximate optimal tour for each subproblem is searched by a local search technique. Moreover, these tours obtained for the subproblems are properly connected to form a feasible tour based on a specifically-designed connection scheme. Furthermore, a new mutation operator is designed and used to improve each connected feasible tour further. The global convergence of the proposed algorithm is proved. At last, the simulations are made for several problems and the results indicate the proposed algorithm is effective.