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

Authors

Huang Xia, 1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;;2. Zhangjiagang Campus, Jiangsu University of Science and Technology, Zhangjiagang 215600, China;
Chunming Ye, 1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;;
Cao Lei, 1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;;

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.

Recommended Citation

Xia, Huang; Ye, Chunming; and Lei, Cao (2020) "Invasive Weed Optimization Algorithm Combined with Chaotic Mutation and Analysis of Its Property," Journal of System Simulation: Vol. 28: Iss. 8, Article 4.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss8/4

First Page

1732

Revised Date

2015-08-25

DOI Link

https://doi.org/

Last Page

1740

CLC

TP301.6

Recommended Citation

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.