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Open AccessArticle

Particle Swarm Contour Search Algorithm

Faculty of Computer Science, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany
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Entropy 2020, 22(4), 407; https://doi.org/10.3390/e22040407
Received: 31 January 2020 / Revised: 30 March 2020 / Accepted: 30 March 2020 / Published: 2 April 2020
(This article belongs to the Special Issue Unconventional Methods for Particle Swarm Optimization)
In this article, we present a new algorithm called Particle Swarm Contour Search (PSCS)—a Particle Swarm Optimisation inspired algorithm to find object contours in 2D environments. Currently, most contour-finding algorithms are based on image processing and require a complete overview of the search space in which the contour is to be found. However, for real-world applications this would require a complete knowledge about the search space, which may not be always feasible or possible. The proposed algorithm removes this requirement and is only based on the local information of the particles to accurately identify a contour. Particles search for the contour of an object and then traverse alongside using their known information about positions in- and out-side of the object. Our experiments show that the proposed PSCS algorithm can deliver comparable results as the state-of-the-art. View Full-Text
Keywords: particle swarm optimisation; contour search; flat landscape; multi-modal particle swarm optimisation; contour search; flat landscape; multi-modal
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Weikert, D.; Mai, S.; Mostaghim, S. Particle Swarm Contour Search Algorithm. Entropy 2020, 22, 407.

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