Circle混沌映射协同随机游走的混合白鲨优化算法

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中图分类号：TP18 文献标识码：A 文章编号：2096-4706（2025）18-0065-05

Abstract：The initial population qualityof the White Shark Optimizer（WSO）algorithm is poor，and it is easyto fall into localoptima.Byadding Circlechaotic mapping，the population diversityofthe WSOalgorithm inthe initializationstage is improved，andtherandomwalkstrategyis triggeredwithacertainprobabilitywhichelpsthealgorithmjumpoutofthe local optimal beter.The experimentalverification is conducted basedon the CEC2022 benchmark test functions.Through comparativeanalysis with various intellgent optimization algorithms，it is found that the improved WSO algorithm exhibits relativelyoutstandingperformance metrics.Theexperimentaldataindicate thattheproposedalgorithmachieves highersolution accuracyandfasterconvergencespeed，whilealsodemonstratingsuperiorstabilitycomparedtoothercomparativealgorithms. The effectiveness of the improved algorithm is proved.

Keywords： White Shark Optimizer; CEC2022 benchmark test function; Circle chaotic mapping; random walk strategy

0 引言

随着社会和科技的不断进步，工程和学术等领域都存在着日益复杂的优化问题。（剩余5601字）