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A Hybrid bees algorithm with grasshopper optimization algorithm for optimal deployment of wireless sensor networks

A Hybrid bees algorithm with grasshopper optimization algorithm for optimal deployment of wireless sensor networks
Recurso electrónico / Electronic resource
Registro MARC
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1001 ‎$0‎MAPA20210005596‎$a‎Deghbouch, Hicham
24512‎$a‎A Hybrid bees algorithm with grasshopper optimization algorithm for optimal deployment of wireless sensor networks‎$c‎Hicham Deghbouch, Fatima Debbat
520  ‎$a‎This work addresses the deployment problem in Wireless Sensor Networks (WSNs) by hybridizing two metaheuristics, namely the Bees Algorithm (BA) and the Grasshopper Optimization Algorithm (GOA). The BA is an optimization algorithm that demonstrated promising results in solving many engineering problems. However, the local search process of BA lacks ecient exploitation due to the random assignment of search agents inside the neighborhoods, which weakens the algorithm's accuracy and results in slow convergence especially when solving higher dimension problems. To alleviate this shortcoming, this paper proposes a hybrid algorithm that utilizes the strength of the GOA to enhance the exploitation phase of the BA. To prove the eectiveness of the proposed algorithm, it is applied for WSNs deployment optimization with various deployment settings. Results demonstrate that the proposed hybrid algorithm can optimize the deployment of WSN and outperforms the state-of-the-art algorithms in terms of coverage, overlapping area, average moving distance, and energy consumption.
650 4‎$0‎MAPA20080553128‎$a‎Algoritmos
650 4‎$0‎MAPA20080611200‎$a‎Inteligencia artificial
650 4‎$0‎MAPA20170006497‎$a‎Computación cognitiva
7001 ‎$0‎MAPA20210005602‎$a‎Debbat, Fatima
7730 ‎$w‎MAP20200034445‎$t‎Revista Iberoamericana de Inteligencia Artificial‎$d‎IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-‎$x‎1988-3064‎$g‎15/02/2021 Volumen 24 Número 67 - febrero 2021 , p. 18-35
856  ‎$q‎application/pdf‎$w‎1110629‎$y‎Recurso electrónico / Electronic resource