Abstract
It is well known that determining visual sensors in 2D space can be often modeled as an Art Gallery problem. Tasks such as surveillance dictate the coverage of the interior of a non-convex polygon with the optimal number of sensors. The optimal sensor placement is a difficult combinatorial optimization problem, and it can be formulated as seeking the smallest number of sensors obliged to cover every point in a heterogeneous setting. In this article, we propose a suboptimal deterministic algorithm, as well as an adapted differential evolution algorithm for tackling sensor placement. Both versions of novel algorithms have been implemented and tested over hundreds of random polygons. According to the outcomes presented in the experimental analysis, it can be noticed that the approach based on differential evolution beats the deterministic technique as well as other stochastic optimization algorithms for practically all instances.
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Alihodzic, A., Hasanspahic, D., Tuba, E., Tuba, M. (2022). Application of Adjusted Differential Evolution in Optimal Sensor Placement for Interior Coverage. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 235. Springer, Singapore. https://doi.org/10.1007/978-981-16-2377-6_17
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DOI: https://doi.org/10.1007/978-981-16-2377-6_17
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