Hybrid Flower Pollen Algorithm Based on Modified Search Strategy

Wu Wenbin, L. Zhifeng, Wei Zhenhua
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引用次数: 1

Abstract

The pollen algorithm has many characteristics, such as fewer parameters, easy adjustment, and the excellent search path, and has been applied to many engineering optimization problems. But there are easy to premature convergence, slow convergence and easy to fall into the local optimum and other deficiencies, in order to improve the convergence speed and precision of the algorithm, the pollen algorithm is improved in the early stage of the pollen algorithm, the theory of good lattice points is introduced, the pollen gamete are initialized, and the pollen gamete are initialized, In the iterative process, we add the opposition learning mechanism and introduce the improved cross strategy and the Gaussian disturbance strategy of the genetic algorithm in the optimal position, and propose a hybrid pollen algorithm based on modified search strategy based on the improved search strategy(HMFPA). The HMFPA algorithm and the FPA algorithm are simulated by four typical complex test functions in the optimization problem. The results show that the convergence speed and accuracy of the HMFPA algorithm are better than those of the FPA algorithm.
基于改进搜索策略的杂交花粉算法
花粉算法具有参数少、调整方便、搜索路径优等特点,已应用于许多工程优化问题。但存在容易过早收敛、收敛速度慢和易陷入局部最优等不足,为了提高算法的收敛速度和精度,在花粉算法的早期阶段对花粉算法进行了改进,引入了良好格点理论,对花粉配子进行初始化,并对花粉配子进行初始化,在迭代过程中,在遗传算法的最优位置加入对立学习机制,并引入改进交叉策略和高斯干扰策略,在改进搜索策略(HMFPA)的基础上提出了一种基于改进搜索策略的混合花粉算法。通过四个典型的复杂测试函数对优化问题中的HMFPA算法和FPA算法进行了仿真。结果表明,HMFPA算法的收敛速度和精度均优于FPA算法。
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