Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm

IEEE Access

卷:7

Yongquan Zhou¹  Qifang Luo¹  Mengyi Lei¹ 

[1] College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, China;

关键词: Enhanced metaheuristic optimization;    flower pollination algorithm;    wind driven;    wind-driven flower pollination algorithm;   

DOI  :  10.1109/ACCESS.2019.2934733

来源: DOAJ

【 摘 要 】

The flower pollination algorithm is a new metaheuristic optimization technique that simulates the pollination behavior of flowers in nature. The global and local search processes of the algorithm are performed by simulating the self-pollination and cross-pollination of flowers. However, the conventional flower pollination algorithm has several limitations. To overcome the problem of slow convergence and prevent the algorithm from becoming stuck around local optimum, this paper describes an enhanced metaheuristic wind-driven flower pollination algorithm (WDFPA). Experiments are conducted using 29 benchmark test functions and two engineering design problems, and the proposed WDFPA is compared against other metaheuristic optimization algorithms and several classical optimization approaches. The results show that WDFPA achieves better performance than the conventional flower pollination algorithm, especially in high-dimensional optimization problems. The convergence speed and accuracy of WDFPA exhibit significant improvements over other metaheuristic algorithms in many of the test cases. Additionally, WDFPA produces optimal results for engineering design problems involving a welded beam and a spring structure.

【 授权许可】

Unknown