CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
A hybrid cultural algorithm with local search for traveling salesman problem
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
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An improved tabu search -- crossover tabu search (CTS), with the angle-based idea of the sweep heuristic to confirm neighborhood, is presented, which is applied for solving a well-known combinatorial optimization problem-the traveling salesman problem (TSP). The key strategies of the CTS are intensification strategy and diversification strategy. Intensification strategies, based on modifying choice rules to encourage move combinations, are used to enhance the efficiency of local search. Diversifications strategies are designed to drive the search into new regions, i.e., exploit the new search spaces. The CTS implement the crossover operator of the genetic algorithm (GA) as the diversification strategy, and the strategy of selecting elite solutions as the intensification strategy. CTS, standard TS, standard TS with intensification strategy and CTS with the angel-based idea of sweep heuristic are used to solve the same TSP problems which come from the library of TSP instances TSPLIB and other three TSP instances of Fogel's path. The results showed the angle-based CTS has better performances than other algorithms.