Artificial Plant Optimization Algorithm with Double Selection Strategies for DV-Hop

Artificial plant optimization algorithm (APOA) is a population-based stochastic optimization algorithm by simulating the plant growing mechanism. In the standard version, there is no furcation in each branch. This phenomenon is confused with the natural tree because in natural tree, each branch maintains many furcations to improve the efficiency of photosynthesis. To avoid this shortcoming, we incorporate two selection strategies into the methodology of the standard version, and propose one new variant called artificial plant optimization algorithm with double selection strategies. Furthermore, to investigate the performance, this new algorithm is applied to optimize the DV-Hop location algorithm. Simulation results show it achieves the better performance than DV-Hop.