Selamoğlu, Birsen İ and Salhi, Abdellah (2016) The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem. In: Studies in Computational Intelligence. Springer International Publishing, pp. 43-61. ISBN 9783319302331. Official URL: https://doi.org/10.1007/978-3-319-30235-5_3
Selamoğlu, Birsen İ and Salhi, Abdellah (2016) The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem. In: Studies in Computational Intelligence. Springer International Publishing, pp. 43-61. ISBN 9783319302331. Official URL: https://doi.org/10.1007/978-3-319-30235-5_3
Selamoğlu, Birsen İ and Salhi, Abdellah (2016) The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem. In: Studies in Computational Intelligence. Springer International Publishing, pp. 43-61. ISBN 9783319302331. Official URL: https://doi.org/10.1007/978-3-319-30235-5_3
Abstract
The Plant Propagation algorithm (PPA), has been demonstrated to work well on continuous optimization problems. In this paper, we investigate its use in discrete optimization and particularly on the well known Travelling Salesman Problem (TSP). This investigation concerns the implementation of the idea of short and long runners when searching for Hamiltonian cycles in complete graphs. The approach uses the notion of k-optimality. The performance of the algorithm on a standard list of test problems is compared to that of the Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and the New Discrete Firefly Algorithm (New DFA). Computational results are included.
Item Type: | Book Section |
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Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 20 Nov 2016 14:29 |
Last Modified: | 05 Dec 2024 22:46 |
URI: | http://repository.essex.ac.uk/id/eprint/18123 |