期刊
SIMULATION MODELLING PRACTICE AND THEORY
卷 119, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.simpat.2022.102591
关键词
Routing; IoT collection networks; Ant colony; Genetic algorithm; Hybrid algorithms
资金
- University of Tabuk [S-1441-0158]
- Deputyship for research and innovation, Ministry of Education in Saudi Arabia [S-1441-0158]
This study investigates and resolves the indoor routing problem of IoT devices using a new hybrid ant-genetic algorithm. The algorithm is evaluated through numerical and statistical tests, as well as simulation and experimental real prototyping, to demonstrate its efficiency compared with existing methods.
Several difficulties are generally encountered when solving many-objective problems (fitted with three or more conflictual objectives) by applying multi-objective algorithms (resolving two or three objectives), especially those related to their performances. These issues are, in fact, related to their increased execution time, to the strength of recombination/mutation variation or even to the degree of convergence and diversity of the solution. In this study, the indoor routing of IoT devices is investigated and resolved using a new hybrid ant-genetic algorithm. The latter is assessed using numerical and statistical tests. Then, simulation and experimental real prototyping are achieved to show the efficiency of the introduced algorithm compared with that of the existing methods.
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