Titlebook: Evolutionary Algorithms, Swarm Dynamics and Complex Networks; Methodology, Perspec Ivan Zelinka,Guanrong Chen Book 2018 Springer-Verlag Gmb

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Improvement of SOMA Algorithm Using Complex Networkscording to complex network analysis. At the end of the chapter, we show the best possible option how to improve standard SOMA algorithm together with results of a statistical test. Proposed improvements can be made (in principle) on arbitrary algorithm, SOMA here is used only for demonstrative purposes.

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Swarm and Evolutionary Dynamics as a Networkased on the obvious similarity between interactions between individuals in a swarm and evolutionary algorithms and for example, users of social networks, linking between web pages, etc. The analogy between individuals in populations in an arbitrary evolutionary algorithm and vertices of a network is

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Evolutionary Dynamics and Its Network Visualization - Selected Examples are a self-organizing migrating algorithm, differential evolution, particle swarm, artificial bee colony and ant colony optimization. The main ideas and steps are discussed here, for more detailed study and understanding references to original research papers are throughout the text. The aim of thi

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Improvement of SOMA Algorithm Using Complex Networkscording to complex network analysis. At the end of the chapter, we show the best possible option how to improve standard SOMA algorithm together with results of a statistical test. Proposed improvements can be made (in principle) on arbitrary algorithm, SOMA here is used only for demonstrative purpo

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Comparison of Vertex Centrality Measures in Complex Network Analysis Based on Adaptive Artificial Benot free of problems of premature convergence and stagnation. The algorithm design constantly strives for improved performance. Next to the efforts of developing EAs based on entirely new principles, the existing EAs are being improved with advanced techniques, which seek to remedy the afore mention