Invasive Weed Optimization Algorithm Combined with Chaotic Mutation and Analysis of Its Property

Abstract

Abstract: Inspired by the reproductive aggressive behavior of weeds in nature, invasive weed optimization algorithm (IWO) was developed as a novel bionic swarm intelligence optimization algorithm. An improved IWO algorithm was proposed on the basis of analyzing bionic principle and limitations of basic IWO, which applied an initialization strategy based on chaotic opposition-based learning, increased the diversity of the population through the mutation operator, and enhanced its ability to jump out of local optimal value by chaotic search around current elites. Simulation results for benchmark functions show that the proposed algorithm has improved optimization property compared with IWO, as an effective method to solve complex function optimization problems in engineering application.

Key words: invasive weed algorithm, bionic principle, chaotic mutation, simulation test

CLC Number:

TP301.6

Huang Xia, Ye Chunming, Cao Lei. Invasive Weed Optimization Algorithm Combined with Chaotic Mutation and Analysis of Its Property[J]. Journal of System Simulation, 2016, 28(8): 1732-1740.

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