Calibration and surrogate model-based sensitivity analysis of crystal plasticity finite element models by Hugh Dorward, David M. Knowles, Eralp Demir, Mahmoud Mostafavi, Matthew J. Peel

“…Comparison of the Nelder-Mead and differential evolution algorithms demonstrated that only the differential evolution algorithm was able to reliably find the global optimum due to the presence of local minima in the calibration objective function. …”
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Conceptual Comparison of Population Based Metaheuristics for Engineering Problems by Oluwole Adekanmbi, Paul Green

“…Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. …”
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BAYESIAN FINITE ELEMENT MODEL UPDATING BASED ON MARKOV CHAIN POPULATION COMPETITION by YE Ling, JIANG HongKang, ZOU YuQing, CHEN HuaPeng, WANG LiCheng

“…The traditional Markov Chain Monte Carlo（MCMC） simulation method is inefficient and difficult to converge in high dimensional problems and complicated posterior probability density.In order to overcome these shortcomings，a Bayesian finite element model updating algorithm based on Markov chain population competition was proposed.First，the differential evolution algorithm was introduced in the traditional method of Metropolis-Hastings algorithm.Based on the interaction of different information carried by Markov chains in the population，optimization suggestions were obtained to approach the objective function quickly.It solves the defect of sampling retention in the updating process of high-dimensional parameter model.Then，the competition algorithm was introduced，which has constant competitive incentives and a built-in mechanism for losers to learn from winners.Higher precision was obtained by using fewer Markov chains，which improves the efficiency and precision of model updating.Finally，a numerical example of finite element model updating of a truss structure was used to verify the proposed algorithm in this paper.Compared with the results of standard MH algorithm，the proposed algorithm can quickly update the high-dimensional parameter model with high accuracy and good robustness to random noise.It provides a stable and effective method for finite element model updating of large-scale structure considering uncertainty.…”
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Improving Forecasts of the EGARCH Model Using Artificial Neural Network and Fuzzy Inference System by Geleta T. Mohammed, Jane A. Aduda, Ananda O. Kube

“…After the simulation, parameter estimation of the proposed model using a differential evolution algorithm on the simulated data is done. …”
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Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
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Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…The paper demonstrates the superiority of the proposed model over the genetic algorithm and differential evolution models. The robustness of the proposed model is evaluated at different production rates. …”
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基于混合蛙跳算法的齿轮传动优化设计 by 何兵, 车林仙, 刘初升

“…The hybrid optimization algorithm（HODEFL） overcame the disadvantages on low precision and premature convergence of shuffled frog leaping algorithm（SFLA） for high-dimensional optimization by taking advantages of strong global search and rapid convergence of DE/best/2/bin（DEb2） in differential evolution algorithm（SDE）.The SFLA and DE are hybridized to form a hybrid optimization algorithm（HODEFL） in order to overcome the disadvantages of the SFLA.The study object is the optimization design of the cylindrical helical gear reducer,establishing minimum volume.By comparing with the improved particle swarm optimization（LWPSO）,SFLA and with DEb2 evolutionary algorithm,the HODEFL algorithm is superior to other three algorithms in terms of optimization efficiency,computational accuracy and robustness.…”
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Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System by Qiang Gao, Jilin Chen, Li Wang, Shiqing Xu, Yuanlong Hou

“…To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. …”
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Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source by P. Sundararaman, E. Mohan, S. V. Aswin Kumer, Sridhar Udayakumar, Abdissa Fekadu Moti

“…The proposed BAT algorithm has been executed with the MATLAB 2016 software and compared with the differential evolution technique for IEEE 33 bus, IEEE 69 bus, and Indian real time 62 bus systems. …”
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Numerical Simulation Study on the Strengthening Mechanism of Rock Materials under Impact Loads by Xin Liu, Kai Wang, Chunan Tang, Xikun Qian

“…The orthogonal design and range method are used to analyze the sensitivity of the dynamic damage constitutive parameters, and a differential evolution algorithm is used to invert the relevant parameters of the constitutive model. …”
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Multi-Objective Optimization of Three-Stage Turbomachine Rotor Based on Complex Transfer Matrix Method by Hüseyin Tarık Niş, Ahmet Yıldız

“…In order to design a more efficient structure of a three-stage turbomachine rotor, we integrated this method with various optimization algorithms, including genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), gravitational search algorithm (GSA), black hole (BH), particle swarm optimization (PSO), Harris hawk optimization (HHO), artificial bee colony (ABC), and non-metaheuristic pattern search (PS). …”
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Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…There are two commonly applied approaches: the Differential Evolution (DE) algorithm and Fuzzy C-Means (FCM). …”
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Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy by Wen FAN, Lian GE, Xiaoting XIAO, Fangji GAN, Xin LAI, Hongxia DENG, Qi HUANG

“…A new fitness function combining differential evolution (DE) algorithm with gray wolf optimization (GWO) algorithm is proposed to form a new hybrid optimization algorithm, named DEGWO. …”
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Multistage Threshold Segmentation Method Based on Improved Electric Eel Foraging Optimization by Yunlong Hu, Liangkuan Zhu, Hongyang Zhao

“…To optimize threshold selection in color image segmentation, this paper proposes a multi-strategy improved Electric Eel Foraging Optimization (MIEEFO). The proposed algorithm integrates Differential Evolution and Quasi-Opposition-Based Learning strategies into the Electric Eel Foraging Optimization, enhancing its search capability, accelerating convergence, and preventing the population from falling into local optima. …”
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Investigation on Evolutionary Computation Techniques of a Nonlinear System by Tran Trong Dao

“…A nonlinear mathematical model is required to describe the dynamic behaviour of batch process; this justifies the use of evolutionary method of the EAs to deal with this process. Four algorithms from the field of artificial intelligent—differential evolution (DE), self-organizing migrating algorithm (SOMA), genetic algorithm (GA), and simulated annealing (SA)—are used in this investigation. …”
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Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment by Lin Wang, Hui Qu, Shan Liu, Cai-xia Dun

“…Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. …”
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Simulating the non-Hermitian dynamics of financial option pricing with quantum computers by Swagat Kumar, Colin Michael Wilmott

“…Although imaginary time evolution is non-unitary, the normalised dynamics of this evolution can be simulated on a quantum computer using the quantum imaginary time evolution (QITE) algorithm. …”
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A Comparative Study on Sideband Optimization in Time-Modulated Arrays by Ertugrul Aksoy, Erkan Afacan

“…During the investigations, differential evolution (DE) algorithm is chosen as the optimization tool. …”
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An Electrochemical/Thermodynamic Analytical Model for Hard‐Pack Lithium‐Ion Batteries in Engineering Education by Ligang Wang, Hangyang Li, Zhiliang Huang, Peng Wu, Jiayuan Huangfu

“…The paper elucidates the mechanisms of electrochemical/thermodynamic behavior evolution in lithium‐ion batteries under thermal abuse and develops a state evaluation model based on ordinary differential equations. …”
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