CSRX: A Novel Crossover Operator for a Genetic Algorithm Applied to the Traveling Salesperson Problem

Author:

Uray MartinORCID,Wintersteller Stefan,Huber StefanORCID

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Asadpour, A., Goemans, M.X., Mźdry, A., Gharan, S.O., Saberi, A.: An Olog n/Log Log n-approximation algorithm for the asymmetric traveling salesman problem. Oper. Res. 65(4), 1043–1061 (2017). https://doi.org/10.5555/3216622.3216635

2. Bliek, L., da Costa, P., Refaei Afshar, R., Zhang, Y., Catshoek, T., Vos, D., Verwer, S., Schmitt-Ulms, F., Hottung, A., Shah, T., Sellmann, M., Tierney, K., Perreault-Lafleur, C., Leboeuf, C., Bobbio, F., Pepin, J., Silva, W., Gama, R., Fernandes, H., Zaefferer, M., López-Ibáñez, M., Irurozki, E.: The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems (2022). http://arxiv.org/abs/2201.10453

3. Davis, L. (ed.): Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York, NY (1991)

4. Dong, X., Cai, Y.: A novel genetic algorithm for large scale colored balanced traveling salesman problem. Future Gen. Comput. Syst. 95, 727–742 (2019). https://doi.org/10.1016/j.future.2018.12.065

5. Fogel, D.B.: Applying evolutionary programming to selected traveling salesman problems. Cybern. Syst. 24(1), 27–36 (1993). https://doi.org/10.1080/01969729308961697

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