Small-world property evaluated by exchanging network topology

Tomoya Suzuki (), Masayuki Okazawa and Kuniaki Ohkura
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Tomoya Suzuki: Department of Intelligent Systems Engineering, College of Engineering, Ibaraki University, 4-12-1 Nakanarisawa-cho, Hitachi, Ibaraki 316-8511, Japan
Masayuki Okazawa: Major in Intelligent Systems Engineering, Graduate School of Science and Engineering, Ibaraki University, 4-12-1 Nakanarisawa-cho, Hitachi, Ibaraki 316-8511, Japan
Kuniaki Ohkura: Major in Intelligent Systems Engineering, Graduate School of Science and Engineering, Ibaraki University, 4-12-1 Nakanarisawa-cho, Hitachi, Ibaraki 316-8511, Japan

International Journal of Modern Physics C (IJMPC), 2015, vol. 26, issue 11, 1-18

Abstract: The present study quantified the degree of the small-world (SW) property defined by Watts, and evaluated its achievement level to characterize complex networks. However, because this process has a combinatorial optimization problem, we applied the chaos neural network (CNN) and the simulated annealing (SA), and confirmed their performance in terms of optimized values and numerical costs. Next, we visualized the original network and its optimized networks whose SW property was maximized or minimized by exchanging the original network topology. As a result, although CNN and SA require huge computational time, we confirmed that they can evaluate the SW property and even real SW networks still have plenty of room to enlarge their own SW property.

Keywords: Small-world networks; combinatorial optimization; chaos-neural network; simulated annealing (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1142/S0129183115501223

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