Abstract: Though flower pollination algorithm is very efficient in solving optimization problems, it can become slow in convergence. To overcome this, a different evolution flower pollination algorithm with a time variant factor（TVDFPA） is presented to enhance the rate of convergence. With the incorporation of the differential evolution strategy in the iterative process, the proposed approach can improve the convergence speed and optimization capabilities. The TVDFPA has been tested using a diverse subset of standard functions, and the simulation results show that the optimization ability of the improved algorithm is significantly better than those of the basic Flower Pollination Algorithm（FPA）, Flower Pollination Algorithm based on Simulated Annealing（SFPA）, Hybridization of Flower Pollination algorithm with Chaotic Harmony Search algorithm（HFPCHS）. Then, the hybrid TVDFPA and double fitness value comparison method with variable parameter has been used to solve the problem of pressure vessel designs. Experimental results show that the improved algorithm has better performance.

Key words: Flower Pollination Algorithm（FPA）, time variant factor, differential evolutionary strategies, double fitness value comparison method with variable parameter, pressure vessel design

摘要： 虽然花授粉算法对于求解优化问题十分有效，但也存在收敛性慢的问题。为了解决此问题，提出一种带有时变因子的差分进化花授粉算法（Differential Evolution Flower Pollination Algorithm with Time Variant Factor，TVDFPA）。对步长因子进行改进，同时在迭代过程中加入差分进化的策略，通过种群杂交，提高算法的收敛速度和寻优能力。通过标准测试函数进行测试，仿真结果表明TVDFPA的收敛速度比原始花授粉算法、混沌和声的花授粉（HFPCHS）、模拟退火花授粉算法（SFPA）快，收敛精度也有较大提高。进而结合花授粉算法的特点，建立带有变参数的双适应值比较法来求解压力容器设计问题，实验结果表明改进之后的算法具有较好的求解性能。

关键词: 花授粉算法, 时变因子, 差分进化策略, 变参双适应值比较法, 压力容器设计