Abstract
Traditionally, the optimization algorithm based on physics principles has some shortcomings such as low population diversity and susceptibility to local extrema. A new optimization algorithm based on kinetic-molecular theory (KMTOA) is proposed. In the KMTOA three operators are designed: attraction, repulsion and wave. The attraction operator simulates the molecular attraction, with the molecules moving towards the optimal ones, which makes possible the optimization. The repulsion operator simulates the molecular repulsion, with the molecules diverging from the optimal ones. The wave operator simulates the thermal molecules moving irregularly, which enlarges the searching spaces and increases the population diversity and global searching ability. Experimental results indicate that KMTOA prevails over other algorithms in the robustness, solution quality, population diversity and convergence speed.
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Foundation item: Project(61174140) supported by the National Natural Science Foundation of China; Project(13JJA002) supported by Hunan Provincial Natural Science Foundation, China; Project(20110161110035) supported by the Doctoral Fund of Ministry of Education of China
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Fan, Cd., Ouyang, Hl., Zhang, Yj. et al. Optimization algorithm based on kinetic-molecular theory. J. Cent. South Univ. 20, 3504–3512 (2013). https://doi.org/10.1007/s11771-013-1875-2
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DOI: https://doi.org/10.1007/s11771-013-1875-2