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.
Supported by: National Natural Science Foundation of China (No. 70571009, 70171040 and 70031020 (key project)), Key Project of Chinese Ministry of Education (No. 03052), Ph.D. Program Foundation of Ministry of Education of China (No. 20010141025).
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Hu, X., Ding, Q., Li, Y., Song, D. (2007). An Improved Ant Colony System and Its Application. In: Wang, Y., Cheung, Ym., Liu, H. (eds) Computational Intelligence and Security. CIS 2006. Lecture Notes in Computer Science(), vol 4456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74377-4_5
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DOI: https://doi.org/10.1007/978-3-540-74377-4_5
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