We propose a new genetic algorithm with optimal recombination for the asymmetric instances of travelling salesman problem. The algorithm incorporates several new features that contribute to its effectiveness: 1. Optimal recombination problem is solved within crossover operator. 2. A new mutation operator performs a random jump within 3-opt or 4-opt neighborhood. 3. Greedy constructive heuristic of Zhang and 3-opt local search heuristic are used to generate the initial population. A computational experiment on TSPLIB instances shows that the proposed algorithm yields competitive results to other well-known memetic algorithms for asymmetric travelling salesman problem.
CITATION STYLE
Eremeev, A. V., & Kovalenko, Y. V. (2018). Genetic algorithm with optimal recombination for the asymmetric travelling salesman problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10665 LNCS, pp. 341–349). Springer Verlag. https://doi.org/10.1007/978-3-319-73441-5_36
Mendeley helps you to discover research relevant for your work.