Abstract
The CHC algorithm uses an elitist selection method which, combined with an incest prevention mechanism and a method to diverge the population whenever it converges, allows the maintenance of the population diversity. This algorithm was successfully used in the past for static optimization problems. In this paper we propose three new and improved CHC-based algorithms designed to deal with dynamic environments. The performance of the investigated CHC algorithms is tested in different instances of the dynamic Traveling Salesman Problem. The experimental results show the efficiency, robustness and adaptability of the improved CHC variants solving different dynamic traveling salesman problems. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Simões, A., & Costa, E. (2011). CHC-based algorithms for the dynamic traveling salesman problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6624 LNCS, pp. 354–363). https://doi.org/10.1007/978-3-642-20525-5_36
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