Because of their superior problem-solving ability,nature-inspired optimization algorithms are being regularly used in solv-ing complex real-world optimization problems.Engineering academics have recently focused on meta-heuristic algorithms to solve various optimization challenges.Among the state-of-the-art algorithms,Differential Evolution(DE)is one of the most successful algorithms and is frequently used to solve various industrial problems.Over the previous 2 decades,DE has been heavily modified to improve its capabilities.Several DE variations secured positions in IEEE CEC competitions,establishing their efficacy.However,to our knowledge,there has never been a comparison of performance across various CEC-winning DE versions,which could aid in determining which is the most successful.In this study,the performance of DE and its eight other IEEE CEC competition-winning variants are compared.First,the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions,and the performances have been compared.One unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems,out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite,have been solved to compare the performances.Statistical analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm's ability statistically.Performance analysis exposes that none of the DE variants can solve all the problems efficiently.Performance of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.

Sanjoy Chakraborty;Apu Kumar Saha;Sushmita Sharma;Saroj Kumar Sahoo;Gautam Pal

Department of Computer Science and Engineering,National Institute of Technology Agartala,Agartala,Tripura 799046,India;Department of Computer Science and Engineering,Iswar Chandra Vidyasagar College,Belonia,Tripura 799155,India;Department of Mathematics,National Institute of Technology Agartala,Agartala,Tripura 799046,India;Department of Computer Science and Engineering,Tripura Institute of Technology,Narsingarh,Tripura 799015,India

仿生工程学报（英文版）

[1]Sanjoy Chakraborty;Apu Kumar Saha;Sushmita Sharma;Saroj Kumar Sahoo;Gautam Pal-.Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems)[J].仿生工程学报（英文版）,2022(04):1140-1160

SHADE,ELSHADE,SPACMA

Comparative,Performance,Analysis,Differential,Evolution,Variants,Engineering,Design,Problems,Because,their,superior,solving,ability,nature,inspired,optimization,algorithms,being,regularly,complex,real,world,problems,academics,have,recently,focused,meta,heuristic,various,challenges,Among,state,art,most,successful,frequently,industrial,Over,previous,decades,has,been,heavily,modified,improve,its,capabilities,Several,variations,secured,positions,IEEE,CEC,competitions,establishing,efficacy,However,knowledge,there,never,comparison,across,winning,versions,which,could,aid,determining,In,this,study,eight,other,variants,compared,First,evaluated,bound,functions,performances,One,unconstrained,from,suite,five,mechanical,engineering,design,out,four,issues,taken,convex,solved,Statistical,analyses,like,Friedman,test,Wilcoxon,executed,verify,statistically,analysis,exposes,that,none,can,efficiently,considerable,among,methods,such

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