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Nature is a rich source of inspiration, which has inspired many researchers in many ways. Nowadays, new algorithms have been developed by the inspiration from nature. The flower pollination algorithm is based on the characteristics of pollination process of flowers plants. Pollination is a natural biological process of mating in plants. In flowers, pollen is carried to stigma through some mechanisms that confirm a proper balance in the genetic creations of the species. Another nature inspired algorithm — the Bat algorithm is based on the echolocation behavior of bats. In this paper, the Flower pollination algorithm is compared with the basic Bat algorithm. We have tested these two algorithms on both unimodal and multimodal, low and high dimensional continuous functions. Simulation results suggest that the Flower pollination algorithm can perform much better than the Bat algorithm on the continuous optimization problems.

A Comparative Study of Flower Pollination Algorithm and Bat Algorithm on Continuous Optimization Problems