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https://hdl.handle.net/20.500.14279/30839
Τίτλος: | Ant Colony Optimization with Local Search for Dynamic Traveling Salesman Problems | Συγγραφείς: | Mavrovouniotis, Michalis Müller, Felipe M. Yang, Shengxiang |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Λέξεις-κλειδιά: | Ant colony optimization (ACO);dynamic traveling salesman problem (DTSP);local search;memetic algorithm | Ημερομηνία Έκδοσης: | 1-Ιου-2017 | Πηγή: | IEEE Transactions on Cybernetics, vol. 47, iss. 7, pp. 1743 - 1756 | Volume: | 47 | Issue: | 7 | Start page: | 1743 | End page: | 1756 | Περιοδικό: | IEEE Transactions on Cybernetics | Περίληψη: | For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms. | URI: | https://hdl.handle.net/20.500.14279/30839 | ISSN: | 21682267 | DOI: | 10.1109/TCYB.2016.2556742 | Rights: | © IEEE | Type: | Article | Affiliation: | De Montfort University Federal University |
Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Άρθρα/Articles |
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