首页|A Differential Evolution Flower Pollination Algorithm with Dynamic Switch Probability

A Differential Evolution Flower Pollination Algorithm with Dynamic Switch Probability

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For the shortcomings of the basic flower pollination algorithm, this paper proposes a differential evolution flower pollination algorithm with dynamic switch probability based on the Weibull distribution. This new algorithm improved the convergence rate and precision. The switch probability is improved by Weibull distribution function combined with the number of iterations. It can balance the relationship between the global pollination and the local pollination to improve the overall optimization performance of the algorithm. Random mutation operator is merged into the global pollination process to increase diversity of the population, enhance the ability of the algorithm's global search and avoid premature convergence. In the process of local pollination, directed mutation and crossover operation of the differential evolution are incorporated, it makes the individual flower position update with the memory function, which can choose the direction of variation reasonably. The use of cross-operation can avoid new solutions crossing the boundary. Convergence rate is improved and the algorithm can approach the global optimal solution continuously. Theoretical analysis proved the convergence and time complexity of the improved algorithm. The simulation results based on the function optimization problem show that the improved algorithm has better performance of optimization, faster convergence speed and higher convergence accuracy.

Flower pollination algorithmDynamic switch probabilityRandom mutation operatorDifferen-tial evolutionOptimization accuracyConvergence rate

LIU Jingsen、LIU Li、LI Yu

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Institute of Intelligent Network system, Henan University, Kaifeng 475000, China

College of Software, Henan University, Kaifeng 475000, China

Institute of Management Science and Engineering, Henan University, Kaifeng 475000, China

This work is supported by the Science&Technology Program of Henan Province,ChinaThis work is supported by the Science&Technology Program of Henan Province,China

182102310886162102110109

2019

10.1049/cje.2019.04.008

中国电子杂志(英文版)

中国电子杂志(英文版)

CSTPCDCSCDSCIEI
ISSN：1022-4653
年,卷(期)：2019.28(4)
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