Abstract
•Optimizers effectively solve real-world and engineering IoT networks problems.•The introduced routing formulation rely on practical energy assumptions.•A new scheme for hybridizing ant colony and genetic algorithms is proposed.•The introduced hybridization outperforms the original algorithms.•The behavior of the hybrid model is compared with other recent optimizers.
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.