Abstract
In this paper we present a Swarm Search Algorithm with varying population of agents based on a previous model with fixed population which proved its effectiveness on several computation problems [6,7,8]. We will show that the variation of the population size provides the swarm with mechanisms that improves its self-adaptability and causes the emergence of a more robust self-organized behavior, resulting in a higher efficiency on searching peaks and valleys over dynamic search landscapes represented here by several three-dimensional mathematical functions that suddenly change over time.
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Fernandes, C., Ramos, V., Rosa, A.C. (2005). Varying the Population Size of Artificial Foraging Swarms on Time Varying Landscapes. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_49
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DOI: https://doi.org/10.1007/11550822_49
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