A solution of TSP based on the improved ant colony optimization

Author:

Nie Hengyu1ORCID,Li Meijuan1ORCID,Chen Xuebo1ORCID,Cui Zaihui2ORCID

Affiliation:

1. School of Electronic Information and Engineering, University of Science and Technology Liaoning, China

2. School of Artificial Intelligence, Anshan Normal University, China

Publisher

ACM

Reference22 articles.

1. A genetic algorithm for the close-enough traveling salesman problem with application to solar panels diagnostic reconnaissance;Placido A. Di;Computers,2022

2. Discrete comprehensive learning particle swarm optimization algorithm with Metropolis acceptance criterion for traveling salesman problem

3. Heterogeneous ant colony optimization based on adaptive interactive learning and non-zero-sum game

4. F. Valdez , F. Moreno , P. J. H. i. s. i. c. Melin, pattern recognition, and medicine, "A comparison of ACO , GA and SA for solving the TSP problem," Hybrid intelligent systems in control, pattern recognition medicine , pp. 181 - 189 , 2020 . F. Valdez, F. Moreno, P. J. H. i. s. i. c. Melin, pattern recognition, and medicine, "A comparison of ACO, GA and SA for solving the TSP problem," Hybrid intelligent systems in control, pattern recognition medicine, pp. 181-189, 2020.

5. A. Colorni , M. Dorigo , and V. Maniezzo , " Distributed optimization by ant colonies," in Proceedings of the first European conference on artificial life , 1991 , vol. 142 , pp. 134 - 142 : Paris , France . A. Colorni, M. Dorigo, and V. Maniezzo, "Distributed optimization by ant colonies," in Proceedings of the first European conference on artificial life, 1991, vol. 142, pp. 134-142: Paris, France.

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