Abstract
Chaotic ant swarm optimization (CASO) is a powerful chaos search algorithm for optimization problems, but it is often easy to be premature convergence. To overcome the weakness, this paper presents a CASO with passive congregation (CASOPC). Passive congregation is one type of biological information sharing mechanisms that allow animals to aggregate into groups and help to enhance the exploitation of animals. By introducing passive congregation strategy into the CASO, a modified evolution equation based on the CASO is proposed in the CASOPC. The modified evolution equation cannot only employ the parallel search of all ants and the well exploration ability of the CASO, but also stress and control the exploitation by passive congregation coefficient c in the stage of evolution. Due to linearly increasing c in the CASOPC, the exploration and exploitation ability of ants are well balanced so that premature convergence can be avoided and good performance can be achieved. In order to estimate the capability of the CASOPC, it is tested with a set of 5 benchmark functions with 30 dimensions and compared to the CASO. Experimental results indicate that the CASOPC improves the search performance on the benchmark functions significantly.
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Li, Y., Wen, Q. & Zhang, B. Chaotic ant swarm optimization with passive congregation. Nonlinear Dyn 68, 129–136 (2012). https://doi.org/10.1007/s11071-011-0209-x
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DOI: https://doi.org/10.1007/s11071-011-0209-x