{"title":"DHRDE:基于双群体混合更新和 RPR 机制的工程应用差分进化算法","authors":"","doi":"10.1016/j.cma.2024.117251","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, an enhanced differential evolution algorithm based on dual population hybrid update and random population replacement strategy (namely RPR mechanism) is proposed, which is called DHRDE. DHRDE algorithm involves three key improvements, first, the elite reverse population is constructed according to the original population before the update phase to uncover more potential areas to be searched. Second, a perturbation mechanism is integrated into the DE/rand/2 approach of the differential evolution algorithm to bolster its search efficiency, two updating models are established using co-leadership of random and locally optimal individuals, and then dual-population hybrid update strategy is adopted to achieve all-round and multi-angle search. Thirdly, using RPR mechanism to operate multiple types of mutations on some populations further improves the convergence accuracy. In order to verify the effectiveness of the proposed algorithm, DHRDE is compared with a variety of different types of algorithms in multi-dimension of the CEC2017, CEC2020 and CEC2022 test set, and statistical analysis is performed by Wilcoxon rank sum test and Friedman test. The results show that DHRDE algorithm has better performance. DHRDE algorithm is also used to solve seven engineering design problems and three PV model parameter estimation problems, the optimization results show that DHRDE algorithm is suitable for different complex problems and has effectiveness. In addition, this paper establishes a smooth path planning model for multi-size robots, and uses DHRDE to solve the model, the results of five groups of simulation experiments show that DHRDE algorithm can provide robot moving trajectories with higher smoothness and shorter paths. Analyzing and comparing the fitness metrics through heat maps, the comparative study demonstrates that the DHRDE algorithm is more advantageous and stronger than other algorithms in solving the smooth path planning model for multi-size robots. The above results show that DHRDE algorithm has better performance and has great advantages and competitiveness in solving engineering application optimization problems.</p></div>","PeriodicalId":55222,"journal":{"name":"Computer Methods in Applied Mechanics and Engineering","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications\",\"authors\":\"\",\"doi\":\"10.1016/j.cma.2024.117251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, an enhanced differential evolution algorithm based on dual population hybrid update and random population replacement strategy (namely RPR mechanism) is proposed, which is called DHRDE. DHRDE algorithm involves three key improvements, first, the elite reverse population is constructed according to the original population before the update phase to uncover more potential areas to be searched. Second, a perturbation mechanism is integrated into the DE/rand/2 approach of the differential evolution algorithm to bolster its search efficiency, two updating models are established using co-leadership of random and locally optimal individuals, and then dual-population hybrid update strategy is adopted to achieve all-round and multi-angle search. Thirdly, using RPR mechanism to operate multiple types of mutations on some populations further improves the convergence accuracy. In order to verify the effectiveness of the proposed algorithm, DHRDE is compared with a variety of different types of algorithms in multi-dimension of the CEC2017, CEC2020 and CEC2022 test set, and statistical analysis is performed by Wilcoxon rank sum test and Friedman test. The results show that DHRDE algorithm has better performance. DHRDE algorithm is also used to solve seven engineering design problems and three PV model parameter estimation problems, the optimization results show that DHRDE algorithm is suitable for different complex problems and has effectiveness. In addition, this paper establishes a smooth path planning model for multi-size robots, and uses DHRDE to solve the model, the results of five groups of simulation experiments show that DHRDE algorithm can provide robot moving trajectories with higher smoothness and shorter paths. Analyzing and comparing the fitness metrics through heat maps, the comparative study demonstrates that the DHRDE algorithm is more advantageous and stronger than other algorithms in solving the smooth path planning model for multi-size robots. The above results show that DHRDE algorithm has better performance and has great advantages and competitiveness in solving engineering application optimization problems.</p></div>\",\"PeriodicalId\":55222,\"journal\":{\"name\":\"Computer Methods in Applied Mechanics and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Methods in Applied Mechanics and Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0045782524005073\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Methods in Applied Mechanics and Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045782524005073","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications
In this paper, an enhanced differential evolution algorithm based on dual population hybrid update and random population replacement strategy (namely RPR mechanism) is proposed, which is called DHRDE. DHRDE algorithm involves three key improvements, first, the elite reverse population is constructed according to the original population before the update phase to uncover more potential areas to be searched. Second, a perturbation mechanism is integrated into the DE/rand/2 approach of the differential evolution algorithm to bolster its search efficiency, two updating models are established using co-leadership of random and locally optimal individuals, and then dual-population hybrid update strategy is adopted to achieve all-round and multi-angle search. Thirdly, using RPR mechanism to operate multiple types of mutations on some populations further improves the convergence accuracy. In order to verify the effectiveness of the proposed algorithm, DHRDE is compared with a variety of different types of algorithms in multi-dimension of the CEC2017, CEC2020 and CEC2022 test set, and statistical analysis is performed by Wilcoxon rank sum test and Friedman test. The results show that DHRDE algorithm has better performance. DHRDE algorithm is also used to solve seven engineering design problems and three PV model parameter estimation problems, the optimization results show that DHRDE algorithm is suitable for different complex problems and has effectiveness. In addition, this paper establishes a smooth path planning model for multi-size robots, and uses DHRDE to solve the model, the results of five groups of simulation experiments show that DHRDE algorithm can provide robot moving trajectories with higher smoothness and shorter paths. Analyzing and comparing the fitness metrics through heat maps, the comparative study demonstrates that the DHRDE algorithm is more advantageous and stronger than other algorithms in solving the smooth path planning model for multi-size robots. The above results show that DHRDE algorithm has better performance and has great advantages and competitiveness in solving engineering application optimization problems.
期刊介绍:
Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.