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A NEW HYBRID GENETIC ALGORITHM FOR MAXIMIZING AREA COVERAGE IN WIRELESS SENSOR NETWORKS

Nabil Boumedine & Sadek Bouroubi

Pesquisa Operacional2026https://doi.org/10.1590/0101-7438.2026.046.00299058article
AJG 1
Weight
0.50

What the paper says

Wireless sensor networks are becoming increasingly important in many fields, such as management and security. They enable the collection and transmission of large volumes of data from a specific area to a data center for processing and analysis. One of the most challenging problems in sensor deployment is determining the optimal placement of each sensor to maximize the coverage area. It has been demonstrated that this problem is NP-hard. Due to its huge complexity, various metaheuristics have been proposed to solve the coverage problem in wireless sensor networks. In this paper, we propose an efficient hybrid genetic algorithm to maximize the coverage area in wireless sensor networks. The proposed approach combines a genetic algorithm with an enhanced simulated annealing algorithm. The efficiency of the proposed algorithm has been tested in 15 benchmark instances taken from the literature and compared with state-of-the-art algorithms.

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https://doi.org/https://doi.org/10.1590/0101-7438.2026.046.00299058

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@article{nabil2026,
  title        = {{A NEW HYBRID GENETIC ALGORITHM FOR MAXIMIZING AREA COVERAGE IN WIRELESS SENSOR NETWORKS}},
  author       = {Nabil Boumedine & Sadek Bouroubi},
  journal      = {Pesquisa Operacional},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1590/0101-7438.2026.046.00299058},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.