A trajectory-based heuristic to solve a three-objective optimization problem for wireless sensor network deployment

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Abstract

Nowadays, wireless sensor networks (WSNs) are widely used in more and more fields of application. However, there are some important shortcomings which have not been solved yet in the current literature. This paper focuses on how to add relay nodes to previously established static WSNs with the purpose of optimizing three important factors: energy consumption, average coverage and network reliability. As this is an NP-hard multiobjective optimization problem, we consider two well-known genetic algorithms (NSGA-II and SPEA2) and a multiobjective approach of the variable neighborhood search algorithm (MO-VNS). These metaheuristics are used to solve the problem from a freely available data set, analyzing all the results obtained by considering two multiobjective quality indicators (hypervolume and set coverage). We conclude that MO-VNS provides better performance on average than the standard algorithms NSGA-II and SPEA2.

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Lanza-Gutiérrez, J. M., Gómez-Pulido, J. A., & Vega-Rodríguez, M. A. (2014). A trajectory-based heuristic to solve a three-objective optimization problem for wireless sensor network deployment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8602, pp. 27–38). Springer Verlag. https://doi.org/10.1007/978-3-662-45523-4_3

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