Probabilistic Prediction of the Complexity of Traveling Salesman Problems Based on Approximating the Complexity Distribution from Experimental Data

Author:

Goloveshkin V. A.,Zhukova G. N.,Ulyanov M. V.,Fomichev M. I.

Publisher

Pleiades Publishing Ltd

Subject

Control and Systems Engineering,Electrical and Electronic Engineering

Reference25 articles.

1. Ul’yanov, M.V., Resursno-effektivnye komp’yuternye algoritmy. Razrabotka i analiz (Resource-Efficient Computer Algorithms. Development and Analysis), Moscow: Fizmatlit, 2008.

2. Oliver, I.M., Smith, D.J., and Holland, J.R.C., A Study of Permutation Crossover Operators on the Traveling Salesman Problem, Proc. 2nd Int. Conf. on Genetic Algorithms, Hillsdale, New Jersey: Lawrence Erlbaum Associates, 1987, pp. 224–230.

3. Cotta, C., Aldana, J.F., Nebro, A.J., and Troya, J.M., Hybridizing Genetic Algorithms with Branch and Bound Techniques for the Resolution of the TSP, in Artificial Neural Nets and Genetic Algorithms, Pearson, D., Steele, N., Albrecht, R., Eds., New York: Springer-Verlag, 1995, pp. 277–280.

4. Goldberg, D.E. and Lingle, R., Alleles, Loci, and the Travelling Salesman Problem, Proc. 1st Int. Conf. on Genetic Algorithms (ICGA’85), Hillsdale, New Jersey: Lawrence Erlbaum Associates, 1985, pp. 154–159.

5. Sergeev, S.I., Nonlinear Resolving Functions for the Travelling Salesman Problem, Autom. Remote Control, 2013, vol. 74, no. 6, pp. 978–994.

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