Abstract
Locust Swarms are a newly developed multi-optima particle swarm. They were explicitly developed for non-globally convex search spaces, and their non-convergent search behaviours can also be useful for problems with fractal and fractured landscapes. On the 1000-dimensional “FastFractal” problem used in the 2008 CEC competition on Large Scale Global Optimization, Locust Swarms can perform better than all of the methods in the competition. Locust Swarms also perform very well on a real-world optimization problem that has a fractured landscape. The extent and the effects of a fractured landscape are observed with a practical new measurement that is affected by the degree of fracture and the lack of regularity and symmetry in a fitness landscape.
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Chen, S., Lupien, V. (2009). Optimization in Fractal and Fractured Landscapes Using Locust Swarms. In: Korb, K., Randall, M., Hendtlass, T. (eds) Artificial Life: Borrowing from Biology. ACAL 2009. Lecture Notes in Computer Science(), vol 5865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10427-5_23
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DOI: https://doi.org/10.1007/978-3-642-10427-5_23
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