Abstract
This paper proposes a new algorithm called Multimodal Flower Pollination Algorithm (MFPA). Under MFPA, the original Flower Pollination Algorithm (FPA) is enhanced with multimodal capabilities in order to find all possible optima in an optimization problem. The performance of the proposed MFPA is compared to several multimodal approaches considering the evaluation in a set of well-known benchmark functions. Experimental data indicate that the proposed MFPA provides better results over other multimodal competitors in terms of accuracy and robustness.
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Gálvez, J., Cuevas, E. & Avalos, O. Flower Pollination Algorithm for Multimodal Optimization. Int J Comput Intell Syst 10, 627–646 (2017). https://doi.org/10.2991/ijcis.2017.10.1.42
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DOI: https://doi.org/10.2991/ijcis.2017.10.1.42