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A Novel Variant of Moth Flame Optimizer for higher dimensional Optimization Problems

Journal of Bionic Engineering 2023年第5期20卷 2389-2415页

作者： Saroj Kumar Sahoo Sushmita Sharma Apu Kumar Saha Department of Mathematics National Institute of Technology AgartalaJiraniaTripura799046India

Moth Flame Optimization(MFO)is a nature-inspired optimization algorithm,based on the principle of navigation technique of moth toward *** to less parameter and easy implementation,MFO is used in various field to solve optimization ***,for the complex higher dimensional problems,MFO is unable to make a good trade-off between global and local *** overcome these drawbacks of MFO,in this work,an enhanced MFO,namely WF-MFO,is introduced to solve higher dimensional optimization *** a more optimal balance between global and local search,the original MFO’s exploration ability is improved by an exploration operator,namely,Weibull flight *** addition,the local optimal solutions have been avoided and the convergence speed has been increased using a Fibonacci search process-based technique that improves the quality of the solutions ***-nine benchmark functions of varying complexity with 1000 and 2000 dimensions have been utilized to verify the projected *** popular algorithms and MFO versions have been compared to the achieved *** addition,the robustness of the proposed WF-MFO method has been evaluated using the Friedman rank test,the Wilcoxon rank test,and convergence *** to other methods,the proposed WF-MFO algorithm provides higher quality solutions and converges more quickly,as shown by the ***,the proposed WF-MFO has been used to the solution of two engineering design issues,with striking *** improved performance of the proposed WF-MFO algorithm for addressing larger dimensional optimization problems is guaranteed by analyses of numerical data,statistical tests,and convergence performance.

关键词： Moth Flame Optimization(MFO)algorithm Bio-inspired algorithm Fibonacci search method Weibull distribution higher dimensional functions

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