The flowerpollinationalgorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flowerpollination. In this paper, we review the applications of the singleflower Polli...
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The flowerpollinationalgorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flowerpollination. In this paper, we review the applications of the singleflowerpollinationalgorithm (SFPA), Multi-objectiveflowerpollinationalgorithm an extension of the SFPA and the Hybrid of FPA with other bio-inspired algorithms. The review has shown that there is still a room for the extension of the FPA to Binary FPA. The review presented in this paper can inspire researchers in the bio-inspired algorithms research community to further improve the effectiveness of the PFA as well as to apply the algorithm in other domains for solving real life, complex and nonlinear optimization problems in engineering and industry. Further research and open questions were highlighted in the paper. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
The flowerpollinationalgorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flowerpollination. In this paper, we review the applications of the singleflower Polli...
详细信息
The flowerpollinationalgorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flowerpollination. In this paper, we review the applications of the singleflowerpollinationalgorithm (SFPA), Multi-objectiveflowerpollinationalgorithm an extension of the SFPA and the Hybrid of FPA with other bio-inspired algorithms. The review has shown that there is still a room for the extension of the FPA to Binary FPA. The review presented in this paper can inspire researchers in the bio-inspired algorithms research community to further improve the effectiveness of the PFA as well as to apply the algorithm in other domains for solving real life, complex and nonlinear optimization problems in engineering and industry. Further research and open questions were highlighted in the paper.
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