Abstract
The localization problem arises from the need of the elements of a swarm of robots, or of a Wireless Sensor Network (WSN), to determine its position without the use of external references, such as the Global Positioning System (GPS), for example. In this problem, the location is based on calculations that use distance measurements to anchor nodes, that have known positions. In the search for efficient algorithms to calculate the location, some algorithms inspired by nature, such as Genetic Algorithm (GA) and Particle Swarm Optimization Algorithm(PSO), have been used. Accordingly, in order to obtain better solutions to the localization problem, this paper presents the results obtained with the Backtracking Search Optimization Algorithm (BSA) and compares them with those obtained with the GA.
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© 2014 Springer International Publishing Switzerland
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de Sá, A.O., Nedjah, N., de Macedo Mourelle, L. (2014). Genetic and Backtracking Search Optimization Algorithms Applied to Localization Problems. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8583. Springer, Cham. https://doi.org/10.1007/978-3-319-09156-3_51
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DOI: https://doi.org/10.1007/978-3-319-09156-3_51
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