Abstract
The Ant Colony System (ACS) algorithm is vital in solving combinatorial optimization problems. However, the weaknesses of premature convergence and low efficiency greatly restrict its application. In order to improve the performance of the algorithm, the Hybrid Ant Colony System (HACS) is presented by introducing the pheromone adjusting approach, combining ACS with saving and interchange methods, etc. Furthermore, the HACS is applied to solve the Vehicle Routing Problem with Time Windows (VRPTW). By comparing the computational results with the previous findings, it is concluded that HACS is an effective and efficient way to solve combinatorial optimization problems. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Hu, X., Ding, Q., Li, Y., & Song, D. (2007). An improved ant colony system and its application. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4456 LNAI, pp. 36–45). Springer Verlag. https://doi.org/10.1007/978-3-540-74377-4_5
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