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The Locust Swarm Optimization Algorithm

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New Advancements in Swarm Algorithms: Operators and Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 160))

Abstract

In recent years swarm intelligence emulate the behavior of insects or animal. In this chapter, an optimization algorithm called Locust Search (LS) is presented. The LS is inspired of the behavior of the locust swarms. In the algorithm consider two different behaviors: solitary and social. This tow types of behavior interact with each other in ways to allow find solution to a complex optimization problem. In order to illustrate the efficiency and robustness the LS was compared with other well-known optimization algorithms. The algorithm was proved with several benchmark functions.

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Author information

Authors and Affiliations

  1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas

  2. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Fernando Fausto

  3. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Adrián González

Authors
  1. Erik Cuevas
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  2. Fernando Fausto
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  3. Adrián González
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Corresponding author

Correspondence to Erik Cuevas .

Appendix: List of Benchmark Functions

Appendix: List of Benchmark Functions

In Table 5.5, n is the dimension of function, \(f_{opt}\) is the minimum value of the function, and S is a subset of \(R^{n}\). The optimum location \(({\mathbf{x}}_{opt} )\) for functions in Table 5.5 is in \([0]^{n}\), except for \(f_{5}\) with \({\mathbf{x}}_{opt}\) in \([1]^{n}\).

Table 5.5 Unimodal test functions
Full size table

The optimum location \(({\mathbf{x}}_{opt} )\) for functions in Table 5.6, are in \([0]^{n}\), except for \(f_{8}\) in \([420.96]^{n}\) and \(f_{12}\)–\(f_{13}\) in \([1]^{n}\).

Table 5.6 Multimodal test functions
Full size table

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Cuevas, E., Fausto, F., González, A. (2020). The Locust Swarm Optimization Algorithm. In: New Advancements in Swarm Algorithms: Operators and Applications. Intelligent Systems Reference Library, vol 160. Springer, Cham. https://doi.org/10.1007/978-3-030-16339-6_5

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